This document discusses a novel technique for better analysis of ice properties using Kalman filtering. It summarizes previous research on sea ice segmentation using SAR imagery and dual polarization techniques. It proposes using an automated SAR algorithm along with Kalman filtering to more accurately detect sea ice properties from RADARSAT1 and RADARSAT2 imagery data. The document reviews techniques for image segmentation, dual polarization, PMA detection, and related work on sea ice classification using statistical ice properties, edge preserving region models, and object extraction methods.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IRJET-Underwater Image Enhancement by Wavelet Decomposition using FPGAIRJET Journal
This document describes a method for enhancing underwater images using wavelet decomposition and fusion on an FPGA (field programmable gate array). Underwater images often have low contrast and visibility due to light scattering in water. The proposed method performs color correction and contrast enhancement on an input underwater image. It then decomposes the color-corrected and contrast-enhanced images into low and high frequency components using wavelet transforms. Image fusion is performed on the wavelet coefficients to combine the detailed information from both images. The fused image is reconstructed via inverse wavelet transform. Experimental results show the proposed fusion-based approach improves underwater image visibility. Implementing the algorithm on an FPGA provides benefits over general processors for computationally intensive image processing.
IRJET- Analysis of Underwater Image Visibility using White Balance AlgorithmIRJET Journal
1) The document discusses several techniques for analyzing and improving the visibility of underwater images, including white balancing algorithms, red channel methods, and image fusion approaches.
2) White balancing aims to remove unwanted color casts to improve image aspects like color and contrast. Image fusion techniques combine input images and weight maps to enhance color contrast and visibility of distant objects degraded by the underwater medium.
3) The techniques were evaluated using metrics like PSNR and by comparing restored images to originals. Results found white balancing produced high accuracy recovery of important faded features while image fusion generally improved global contrast, color, and details.
Image Denoising Based On Wavelet for Satellite Imagery: A ReviewIJMER
In this paper studied the use of wavelet and their family to denoising images. Satellite images
are extensively used in the field of RS and GIS for land possession, mapping use for planning and
decision support. As of many Satellite image having common problem i.e. noise which hold unwanted
information in an images. Different types of noise are addressing different techniques to denoising
remotely sense images. Noise within the remote sensing images identifying and denoising them is big
challenge before the researcher. Therefore we review wavelet for denoising of the remote sensing
images. Thus implementing wavelet is essential to get much higher quality denoising image. However,
they are usually too computationally demanding. In order to reduce the
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
A Fusion Based Visibility Enhancement of Single Underwater Hazy ImageIJAAS Team
This document summarizes a research paper that proposes a novel method for enhancing the visibility of single underwater images using multimodal discrete wavelet transform (DWT) fusion. The method generates two inputs for the fusion framework by applying contrast enhancement using singular value decomposition and discrete wavelet transform to the hue-saturation-value color space, and color constancy using the shades of gray algorithm. The fused image produced by taking the mean of approximation sub-bands and the maximum of detail sub-bands undergoes further contrast stretching for enhancement. Experimental results demonstrate improved contrast and visibility over other state-of-the-art underwater image enhancement techniques.
Development and Hardware Implementation of an Efficient Algorithm for Cloud D...sipij
This document discusses the development and hardware implementation of an efficient algorithm for cloud detection from satellite images. The algorithm uses an adaptive thresholding approach to segment clouds from background pixels in satellite imagery. It then determines the position of the segmented clouds to calculate cloud coverage percentages. The algorithm was tested on satellite images from Spot4 and Landsat archives. It was implemented on a TMS320C6713 DSK processor using Code Composer Studio and achieved accurate cloud detection and coverage calculation on images with resolutions up to 3600x3000 pixels.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses using discrete wavelet transform (DWT) and principal component analysis (PCA) as decorrelating transforms for hyperspectral image classification under JPEG2000 compression. It compares the classification performance of DWT and PCA when applying lossless compression and two JPEG2000 scalability options: color and quality. Color scalability decompresses a subset of bands, while quality scalability assigns more bits to important bands. The DWT provides similar classification to PCA but is faster and does not require additional files. Reordering bands by variance before color decompression improved DWT classification results compared to using the initial DWT band order.
This is the project report for my internship at HBCSE-TIFR. The project describes a low-cost method for analysing the spectrum of LEDs and determining the wavelength.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
RADAR Images are strongly preferred for analysis of geospatial information about earth surface to assesse envirmental conditions radar images are captured by different remote sensors and that images are combined together to get complementary information. To collect radar images SAR(Synthetic Aperture Radar) sensors are used which are active sensors and can gather information during day and night without affecting weather conditions. We have discussed DCT and DWT image fusion methods,which gives us more informative fused image simultaneously we have checked performance parameters among these two methods to get superior method from these two techniques
This lecture is about particle image velocimetry technique. It include discussion about the basic element of PIV setup, image capturing, laser lights, synchronize and correlation analysis.
Satellite Image Enhancement Using Dual Tree Complex Wavelet TransformjournalBEEI
Drawback of losing high frequency components suffers the resolution enhancement. In this project, wavelet domain based image resolution enhancement technique using Dual Tree Complex Wavelet Transform (DT-CWT) is proposed for resolution enhancement of the satellite images. Input images are decomposed by using DT-CWT in this proposed enhancement technique. Inverse DT-CWT is used to generate a new resolution enhanced image from the interpolation of high-frequency sub band images and the input low-resolution image. Intermediate stage has been proposed for estimating the high frequency sub bands to achieve a sharper image. It has been tested on benchmark images from public database. Peak Signal-To-Noise Ratio (PSNR) and visual results show the dominance of the proposed technique over the predictable and state-of-art image resolution enhancement techniques.
Image resolution enhancement by using wavelet transform 2IAEME Publication
This document discusses techniques for enhancing the resolution of digital images using wavelet transforms. It proposes a method that uses both stationary wavelet transform (SWT) and discrete wavelet transform (DWT) to decompose an input image into subbands, which are then interpolated using Lanczos interpolation before being combined via inverse DWT. The method is shown to achieve higher peak signal-to-noise ratios than traditional interpolation techniques like bilinear and bicubic interpolation as well as other wavelet-based super resolution methods, demonstrating its effectiveness for image resolution enhancement.
IRJET- Satellite Image Resolution Enhancement using Dual-tree Complex Wav...IRJET Journal
1) A technique for enhancing the resolution of satellite images using dual-tree complex wavelet transform (DT-CWT) and non-local mean (NLM) filtering is proposed.
2) The low-resolution input image is decomposed using DT-CWT into high and low frequency subbands. Lanczos interpolation is used to interpolate the subbands.
3) NLM filtering is then applied to reduce artifacts from the DT-CWT. The filtered subbands are combined using inverse DT-CWT to generate the enhanced, high-resolution image.
4) Experimental results show the proposed technique achieves better resolution enhancement than conventional methods in terms of lower MSE and higher PSNR values.
Image Resolution Enhancement by using Wavelet TransformIRJET Journal
This document presents a technique for enhancing the resolution of low resolution images using wavelet transforms. It decomposes low resolution images into sub-bands using discrete wavelet transform (DWT) and stationary wavelet transform (SWT). The high frequency sub-bands produced by DWT are interpolated and corrected using the high frequency sub-bands from SWT. An inverse DWT is then applied to combine the interpolated sub-bands and produce a higher resolution output image. The technique is compared to conventional methods like bilinear and bicubic interpolation as well as state-of-the-art resolution enhancement techniques. It is shown to produce higher quality results measured using metrics like peak signal-to-noise ratio. The technique has applications in
Applying edge density based region growing with frame difference for detectin...eSAT Publishing House
1. The document presents a method for detecting moving objects in video surveillance systems using edge density based region growing with frame difference.
2. It involves preprocessing frames through edge detection, frame differencing to eliminate stationary backgrounds, and applying edge density based region growing to connect regions of moving objects.
3. Experimental results on videos of a moving person and cylinder show the method can accurately detect moving objects in complex backgrounds.
A NOVEL ALGORITHM FOR IMAGE DENOISING USING DT-CWT sipij
This paper addresses image enhancement system consisting of image denoising technique based on Dual Tree Complex Wavelet Transform (DT-CWT) . The proposed algorithm at the outset models the noisy remote sensing image (NRSI) statistically by aptly amalgamating the structural features and textures from it. This statistical model is decomposed using DTCWT with Tap-10 or length-10 filter banks based on
Farras wavelet implementation and sub band coefficients are suitably modeled to denoise with a method which is efficiently organized by combining the clustering techniques with soft thresholding - softclustering technique. The clustering techniques classify the noisy and image pixels based on the
neighborhood connected component analysis(CCA), connected pixel analysis and inter-pixel intensity variance (IPIV) and calculate an appropriate threshold value for noise removal. This threshold value is used with soft thresholding technique to denoise the image .Experimental results shows that that the
proposed technique outperforms the conventional and state-of-the-art techniques .It is also evaluated that the denoised images using DTCWT (Dual Tree Complex Wavelet Transform) is better balance between smoothness and accuracy than the DWT.. We used the PSNR (Peak Signal to Noise Ratio) along with
RMSE to assess the quality of denoised images.
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A new approach of edge detection in sar images using region based active cont...eSAT Journals
Abstract This paper presents a new methodology for the edge detection of complex radar images. The approach includes the edge improvisation algorithm and followed with edge detection. The nature of complex radar images made edge enhancement part before the edge detection as the data is highly heterogeneous in nature. Thus, the use of discrete wavelet transform in the edge improvisation algorithm is justified. Then region based active contour model is used as edge detection algorithm. The paper proposes the distribution fitting energy with a level set function and neighborhood means and variances as variables. The performance is tested by applying it on different images and the results are been analyzed. Keywords: Edge detection, Edge improvisation, Synthetic Aperture radar (SAR), wavelet transforms.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
SAR ICE IMAGE CLASSIFICATION USING PARALLELEPIPED CLASSIFIER BASED ON GRAM-SC...cscpconf
Synthetic Aperture Radar (SAR) is a special type of imaging radar that involves advanced technology and complex data processing to obtain detailed images from the lake surface. Lake ice typically reflects more of the radar energy emitted by the sensor than the surrounding area, which makes it easy to distinguish between the water and the ice surface. In this research work, SAR images are used for ice classification based on supervised and unsupervised classification
algorithms. In the pre-processing stage, Hue saturation value (HSV) and Gram–Schmidt spectral sharpening techniques are applied for sharpening and resampling to attain highresolution
pixel size. Based on the performance evaluation metrics it is proved that GramSchmidt spectral sharpening performs better than sharpening the HSV between the boundaries.
In classification stage, Gram–Schmidt spectral technique based sharpened SAR images are used as the input for classifying using parallelepiped and ISO data classifier. The performances of the classifiers are evaluated with overall accuracy and kappa coefficient. From the experimental results, ice from water is classified more accurately in the parallelepiped supervised classification algorithm.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
The document reviews techniques for reducing speckle noise in synthetic aperture radar (SAR) data. It begins by describing the characteristics of speckle noise and its multiplicative nature. It then discusses common spatial domain filtering techniques for SAR data denoising, including Lee filtering, Frost filtering, and Kuan filtering. These are adaptive filters that estimate pixel values based on statistics within a moving window. The document also reviews wavelet-based denoising techniques and their advantages over spatial domain filters, including better preservation of edges. Finally, it provides an overview of future research opportunities in developing new speckle reduction methods.
Conceptual and Practical Examination of Several Edge Detection StrategiesIRJET Journal
The document discusses various edge detection techniques for image segmentation. It begins with an introduction to edge detection and image segmentation. Edge detection aims to identify boundaries between different regions in an image and is an important step in image segmentation.
The document then covers the main approaches to edge detection - gradient-based and Laplacian-based. It explains these approaches and provides examples. Some commonly used edge detection techniques are also described - Roberts Cross, Sobel, Prewitt, Laplacian of Gaussian (LoG), and Canny. The steps involved in general edge detection processes like filtering, enhancement and detection are outlined.
Advantages and disadvantages of different edge detection techniques are analyzed. Comparisons of techniques are made through software experiments
AN EFFICIENT IMPLEMENTATION OF TRACKING USING KALMAN FILTER FOR UNDERWATER RO...IJCSEIT Journal
The exploration of oceans and sea beds is being made increasingly possible through the development of
Autonomous Underwater Vehicles (AUVs). This is an activity that concerns the marine community and it
must confront the existence of notable challenges. However, an automatic detecting and tracking system is
the first and foremost element for an AUV or an aqueous surveillance network. In this paper a method of
Kalman filter was presented to solve the problems of objects track in sonar images. Region of object was
extracted by threshold segment and morphology process, and the features of invariant moment and area
were analysed. Results show that the method presented has the advantages of good robustness, high
accuracy and real-time characteristic, and it is efficient in underwater target track based on sonar images
and also suited for the purpose of Obstacle avoidance for the AUV to operate in the constrained
underwater environment.
Pixel Classification of SAR ice images using ANFIS-PSO Classifierijeei-iaes
Synthetic Aperture Radar (SAR) is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN), Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS) classifier and proposed ANFIS with Particle Swarm Optimization (PSO) classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.
A New Approach of Iris Detection and RecognitionIJECEIAES
This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen’s Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image Classification For SAR Images using Modified ANNIRJET Journal
This document discusses using a modified artificial neural network (ANN) for image classification of synthetic aperture radar (SAR) images. Specifically:
- It proposes using a modified ANN with feed forward backpropagation for SAR image classification to identify 9 different land cover types.
- SAR images have benefits over optical images like operating in all weather and having clearer outlines and textures, but speckle noise makes classification difficult.
- The document reviews previous research on SAR image classification using methods like maximum likelihood, ANN, fuzzy techniques. It finds need for improved statistical modeling and more than 6 training sites.
- The proposed modified ANN approach is tested in MATLAB on SAR images to classify pixels into land cover categories
Hardware Unit for Edge Detection with Comparative Analysis of Different Edge ...paperpublications3
Abstract: An edge in an image is a contour across which the brightness of the image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. Edge detection is an important task in image processing. It is a main tool in pattern recognition, image segmentation, and scene analysis. An edge detector is basically a high pass filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many achievements have been made. Many researchers provided different approaches based on mathematical calculations which some of them are either robust or cost effective. A new algorithm will be proposed to detect the edges of image with increased robustness and throughput. Using this algorithm we will reduce the time complexity problem which is faced by previous algorithm. We will also propose hardware unit for proposed algorithm which will reduce the area, power and speed problem. We will compare our proposed algorithm with previous approach. For image quality measurement we will use some scientific parameters those are PSNR, SSIM, FSIM. Implementation of proposed algorithm will be done by Matlab and hardware implementation will be done by using of Verilog on Xilinx 14.1 simulator. Verification will be done on Model sim.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses dimensionality reduction techniques for hyperspectral data in target detection applications. It presents an innovative technique called IRVE-SRRE that aims to preserve rare vectors which may indicate targets of interest, unlike traditional methods. The technique estimates the subspace of abundant background vectors then identifies the rare vectors subspace. It was tested on a case study and shown to estimate the subspace rank accurately while being more computationally efficient than existing techniques like MOCA. The technique could improve target detection algorithms and further research may expand its applications.
A Flexible Scheme for Transmission Line Fault Identification Using Image Proc...IJEEE
This paper describes a methodology that aims to find and diagnosing faults in transmission lines exploitation image process technique. The image processing techniques have been widely used to solve problem in process of all areas. In this paper, the methodology conjointly uses a digital image process Wavelet Shrinkage function to fault identification and diagnosis. In other words, the purpose is to extract the faulty image from the source with the separation and the co-ordinates of the transmission lines. The segmentation objective is the image division its set of parts and objects, which distinguishes it among others in the scene, are the key to have an improved result in identification of faults.The experimental results indicate that the proposed method provides promising results and is advantageous both in terms of PSNR and in visual quality.
Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the Sy...IJERA Editor
Synthetic aperture radar (SAR) Ship Detection System SDS is an important application from the point of view of Maritime Security monitoring. It allows monitoring traffic, fisheries, naval warfare. Since full-resolution SAR images are heavily affected by the presence of speckle, ship detection algorithms generally employ speckle reduced SAR images at the expense of a degradation of the spatial resolution. The proposed Parzen-window-kernel-based algorithm and CFAR algorithm can be considered an alternative to manual inspection for large ocean areas. Promising results and high detection rates for the ships have been achieved. In Parzen-window-kernel-based algorithm for ship detection in synthetic aperture radar (SAR) images, first, the data-driving kernel functions of Parzen window are utilized to approximate the histogram of real SAR image, in order to complete the accurate modeling of SAR images. Then ship detection is implemented using a Constant False Alarm Rate (CFAR). After detecting threshold, the output is added to edge detection algorithm employed on SAR image. Clearer detection of ship candidates is obtained by applying Parzen-window-kernel-based algorithm by changing its window size. Experimental results show that SDS implemented using CUDA is faster than on CPU.
WAVELET PACKET BASED IRIS TEXTURE ANALYSIS FOR PERSON AUTHENTICATIONsipij
There is considerable rise in the research of iris recognition system over a period of time. Most of the
researchers has been focused on the development of new iris pre-processing and recognition algorithms for
good quail iris images. In this paper, iris recognition system using Haar wavelet packet is presented.
Wavelet Packet Transform (WPT ) which is extension of discrete wavelet transform has multi-resolution
approach. In this iris information is encoded based on energy of wavelet packets.. Our proposed work
significantly decreases the error rate in recognition of noisy images. A comparison of this work with nonorthogonal Gabor wavelets method is done. Computational complexity of our work is also less as
compared to Gabor wavelets method.
Despeckling of Sar Image using Curvelet TransformIRJET Journal
This document presents a method for reducing speckle noise in synthetic aperture radar (SAR) images using the curvelet transform. SAR images are affected by speckle noise during image capture and transmission. The curvelet transform is used to decompose the SAR image into different scales and orientations. Thresholding is applied to the curvelet coefficients to remove coefficients corresponding to noise. The inverse curvelet transform is then applied to reconstruct the denoised image. Experimental results on SAR images show that the proposed curvelet-based method achieves higher peak signal-to-noise ratio and lower mean squared error than conventional filters, indicating it more effectively removes noise while preserving image detail.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
This document proposes methods for generating electricity from speed breakers. It discusses 5 classifications of speed breaker power generators that use different mechanisms: 1) a chain drive mechanism, 2) a rack and pinion system, 3) direct use of the load through a reciprocating device, 4) a translator and stator topology, and 5) a pressure lever mechanism. The document also outlines the advantages of using speed breakers for power generation such as low cost and maintenance and being a renewable source. Some challenges are also noted such as selecting a suitable generator and dealing with rain damage.
Cassava waste water was used as an admixture to replace distilled water in ratios of 5%, 10%, 15%, and 20% for producing sandcrete blocks. 60 sandcrete blocks of size 450mm x 150mm x 225mm were produced with different admixture ratios and a control with 0% admixture. The blocks were cured for 7, 14, 21, and 28 days and then tested for moisture content, specific gravity, water absorption, and compressive strength. Test results showed that blocks with 20% cassava waste water admixture met the minimum compressive strength requirement of 3.30 N/mm2 set by Nigerian standards, indicating the potential of cassava waste water to improve sandcrete block quality and
The document presents a theorem on random fixed points in metric spaces. It begins with introductions to fixed point theory, random fixed point theory, and relevant definitions. The main result is Theorem 3.1, which proves that if a self-mapping E on a complete metric space X satisfies certain contraction conditions involving parameters between 0 and 1, then E has a unique fixed point. The proof constructs a Cauchy sequence that converges to the unique fixed point. The document contributes to the study of random equations and random fixed point theory, which has applications in nonlinear analysis, probability theory, and other fields.
1. The document discusses applying multi-curve reconstruction technology to seismic inversion to improve accuracy and reliability. It focuses on reconstructing SP and RMN curves from well logs that are affected by various distortions.
2. The process of reconstructing the curves involves removing baseline drift, standardizing values, applying linear filtering, and fitting the curves. This removes interference and retains valid lithological information.
3. Reconstructing high quality curves improves the resolution and credibility of seismic inversion results. The method is shown to effectively predict sand distribution with little error.
This document compares the performance of a Minimum-Mean-Square-Error (MMSE) adaptive receiver and a conventional Rake receiver for receiving Ultra-Wideband (UWB) signals over a multipath fading channel. It first describes the UWB pulse shapes and channel model used, including the 6th derivative of the Gaussian pulse and the IEEE 802.15.3a modified Saleh-Valenzuela channel model. It then discusses the Direct-Sequence and Time-Hopping transmission and multiple access schemes for UWB. The document presents the receiver structures for the MMSE adaptive receiver and Rake receiver and compares their performance using MATLAB simulations.
This document summarizes a study on establishing logging interpretation models for reservoir parameters like porosity, permeability, oil saturation, and gas saturation in the Gaotaizi Reservoir of the L Oilfield. Models were developed using core data from 4 wells and include:
1) A porosity model relating acoustic travel time to porosity with an error of 0.92%
2) A permeability model relating permeability to porosity with an error of 0.31%
3) An oil saturation model using resistivity data with empirically determined parameters
4) A method to determine original gas saturation from mercury injection data.
Application of the models improved interpretation precision and allowed recalculation of oil and gas reserves for the
This document discusses predicting spam videos on social media platforms using machine learning. It proposes using attributes like number of likes, comments, and view count to classify videos as spam or not spam. A predictive algorithm is developed that uses threshold values for attributes and natural language processing of comments to classify videos. Testing of the algorithm on a dataset achieved a spam prediction precision of 93.6%. Issues with small datasets decreasing accuracy are also discussed, along with continuing work to address this issue.
1) The study experimentally evaluated the compatibility relationship between polymer solutions and oil layers through core flooding tests with different permeability cores.
2) The results showed that injection rate decreased with increasing polymer concentration and molecular weight, and increased with permeability.
3) Based on the results, boundaries for injection capability were established and a compatibility chart was proposed to guide polymer solution selection for different sedimentary microfacies in the field based on permeability and pore size.
1. The document discusses the identification of lithologic traps in the D3 Member of the Gaonan Region using seismic attribute analysis, acoustic impedance inversion, and sedimentary microfacies analysis.
2. Several lithologic traps were identified in the I and II oil groups of the D3 Member, with the largest trap located between wells G46 and G146X1 covering an area of about 2.35 km2.
3. Impedance inversion, seismic attribute analysis, and sedimentary microfacies characterization using 3D seismic data helped determine the location and development of effective lithologic traps in the thin sandstone-shale interbeds of the target stratum.
This document examines using coal ash as a partial replacement for cement in concrete. Coal ash was substituted for cement at rates of 5%, 10%, and 15% by weight. Testing found that concrete with a 5% substitution of coal ash exhibited only a slight decrease in compressive strength of 2% at 28 days while gaining improved workability. Higher substitution rates of 10% and 15% coal ash led to greater decreases in compressive and tensile strength. The study concludes that a 5% substitution of coal ash for cement provides benefits of reduced cost and improved workability with minimal strength impacts, representing an effective use of a waste material that addresses sustainability.
Accounting professional judgment involves handling accounting events and compiling financial reports according to regulations and standards. However, professional judgment is sometimes manipulated to distort accounting information. The document discusses three ways manipulation occurs: 1) abandoning accounting principles, 2) optional changes to accounting policies, and 3) abuse of accounting estimates. The causes of manipulation include distorted motivations from corporate governance issues and catering to various stakeholder interests. Strengthening supervision and improving the accounting system are proposed to manage manipulation of professional judgment.
The document discusses research on the distribution of oil and water in the eastern block of the Chao202-2 area in China. It establishes standards for identifying oil, poor oil, dry, and water layers using well logging data. Analysis shows structural reservoirs are dominant and fault and sand body configuration control oil-water distribution. Oil-water distribution varies between fault blocks from "up oil, bottom water" to "up water, bottom oil" depending on structure and sand body development.
The document describes an intelligent fault diagnosis system for reciprocating pumps that uses pressure and flow signals as inputs. It consists of hardware for data acquisition and a software system for signal processing, feature extraction, and fault diagnosis using wavelet neural networks. The system was able to accurately diagnose three main fault types - seal ring faults, valve damage, and spring faults - based on differences observed in the pressure curves. Testing on over 12 samples of each fault type achieved a correct diagnosis rate of over 94%. The system provides a fast and effective means of remotely monitoring reciprocating pumps and identifying faults.
This document discusses the application of meta-learning algorithms in banking sector data mining for fraud detection. It proposes using Classification and Regression Tree (CART), AdaBoost, LogitBoost, Bagging and Dagging algorithms for classification of banking transaction data. The experimental results show that Bagging algorithm has the best performance with the lowest misclassification rate, making it effective for banking fraud detection through data mining. Data mining can help banks detect patterns for applications like credit scoring, payment default prediction, fraud detection and risk management by analyzing customer transaction history and loan details.
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F05843238
1. IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org
ISSN (e): 2250-3021, ISSN (p): 2278-8719
Vol. 05, Issue 08 (August. 2015), ||V4|| PP 32-38
International organization of Scientific Research 32 | P a g e
A Novel Technique for the better analysis of Ice Properties using
Kalman Filtering
Rajwinder Sidhu1
, Gurbakash Phonsa2
1
Dept of Computer Science and Engineering, Lovely Professional University, Phagwara
1
e-mail:Shilpakaur100@gmail.com
2
Dept of Computer Science and Engineering, Lovely Professional University, Phagwara
2
e-mail: Gurbakash.15483@lpu.co.in
Abstract:SAR algorithm has been used to detect the sea ice to save the ship from any kind of damage. So that
ship does not strike with ice. SAR algorithm applied on RADAR1 imagery data to get accurate results. Pixel
based segmentation MIRGS algorithm to segment the ice has been studied. Due to this we can differentiate the
ice based on its properties. PMA detector has also been studied and thus can easily detect and recognize target
by knowing the signal values. There are many methods for multitemporal segmentation from the MODIS data
called TempoSeg method for multiyear sea ice floes has also been studied. RADARSAT1 imagery data which is
used by Synthetic Aperture Radar to detect the ice of sea at different regions of the oceans. Automated
algorithm gives better result of target using R1 imagery data. In project work, we have to implement the
automated SAR algorithm to detect sea ice which is already implemented. In further work we have to enhance
this automated SAR algorithm to get more accurate results using RADARSAT1 imagery data and will try to use
the RADARSAT2 imagery data to make it compatible to SAR algorithm.
Keywords: Sea Ice, SAR, Floe, Rater Scan, Dual Polarization, Kalman Filtering
I. INTRODUCTION
Processing of an image is a process of translating an image into Digital form into digital form and
applied some operations so that information can be extracted from it. In this entire process input can be any
image, video frame and output can be like features of images and any other things associated with it. Whenever
any functions or signal processing applied on it, image is usually considered as 2D. It is one of the fast growing
technologies. Most of the time this process is known as digital image process but sometimes digital and optical
image processing is also considered [6]. Digital images are manipulated using Digital computers. The main
necessity for image processing of images is that digitized form of image should be available of any finite length
of binary. For digitization, on a discrete grid the given image is sampled and using a finite number of bits each
sample or pixel of image is quantized. Digital images are processed by computers and are converted to Analog
signals for displaying. It is then followed by scanning over some display. Processing is of two types Graphical
and Computer vision based. The Computer Graphics involves the Physical models of lightning, objects and
environment. It is a manual process. It is similar like seemed in a animated movies. But computer vision is often
considered as high-level of Image processing. From this high-level image software tries to extract useful
physical information.
1.1Image Segmentation:
Image segmentation can be defined as the mechanism of subdividing a digital image into multiple
pixels or regions. Regions should greatly reveal to interpret objects. A region is collection of similar pixels. The
aim of segmentation is to represent the image into some meaningful form. There are many different ways to
perform segmentation like thresholding, color based segmentation, watershed segmentation, and texture
methods etc. The Segmentation process involves the partitioning of Digital images into parts. This number could
be N. Segmentation is done based on the pixel sets or the pixels present in a given region. The pixels present are
similar and are based upon the homogeneity of Texture, Colour, and Intensity. This information helps in
locating objects and boundaries in the given image [2]. Segmentation is partitioning a digital image f(a, ab) into
distinct, continuous, and nonempty subsets. After that from these subsets we extract the information of high
level. Practical applications of image segmentation include object identification and recognition, criminal
investigation, medical image processing, facial recognition, satellite images, quality assurance in factories, etc
The two Image Segmentation areas of consideration are:
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1.1.1 Region based segmentation:
Region segmentation can be defined as partitioning the image into regions. Region is an important concept to
depict the image because regions may correspond to objects in the scene. In this, formations of pixels around
some objects are located creating a region of those pixels and separating the region from the rest of the image
[7].
1.1.2 Edge based segmentation:
Edge segmentation can be defined as that in which each object is surrounded by a border. Edge detection is used
to identify the edges and edge pixels. The border of the object is closed, visible and can be detected in the
intensity values of the image. It analyzes the distribution according to gray level value scale [7].
1.2Dual Polarization
RADARSAT 2 is a multichannel receiver. The HH channel of it provides same data as of R1. HV
channel of R2 is a new addition and is anticipated to enhance the bias of ice and water. Unusually, water is wind
roughens and it looks similar to ice at several incidence angles in the channel. Therefore, its required for it to
enhance the sea ice image segmentation results using automated algorithms of SAR. RADARSAT 2 provides all
the features of RADAR1 and offers some additional features to distinguish different ice types [3]. Dual
polarization is the advanced feature which is Radar2 based and is use for mapping of ice. It incorporates 500
km Swath width as that of Radar1 in single polarization. Dual polarization provides Scanning mode of SAR
with additive data [10]. The ENVIST Advance SAR (ASAR) also provides the features of dual polarization bit
it is having different swath width of 100 km from R1 and R2. ASAR has five modes and five different
preferences of polarization levels which can take different images of earth’s surface. We are having a full SAR
scene which contains pixel resolution of 1000*1000 m. Now, we will target on SAR Scan wide mode to
understand the use of R2 dual polarization and will use this model for sea ice monitoring.
1.3 PMA Detector:
In SAR, reflected rays come from target to make it visualize. Point of target will not get if the intensity
or amplitude of reflected rays will not large, usually, because of Lower cluttering signal ratio. Fundamentally,
SCR affects the detection in the presence of amplitude or intensity data. Thus, a good detector should be
designed in such a way that SCR should be improved naturally. Due to this, target can be enhanced and disorder
constrained. We know that, the processor which is mostly used in SPAN detector and this makes only use of
image intensities because the sum of all polar metric channels is incoherent [12]. SPAN detector is having the
synthetic power of all the channels. Therefore, according to some analysis, it has been noticed that this detector
can retrieve a higher SCR and lower noise level than HH, HV, or VV independently. So, we can conclude that
SCR can be improved with the way of synthetic power. Due to this, by using single channel willfull
information; we can single out the targets from the disorder or clutter. For the moment, it is very hard to give the
appropriate detection with the SPAN detector because of the lack of knowledge of related data. Considering
these facts, a PMA detector has constructed as another synthetic power [13].
1.4 Related Work
X.Yang and Clausi(2012)[1] introduces an approach for ice segmentation in Synthetic Aperture Radar (SAR)
generated images. This is done by the combination of Edge Preserving region (EPR) and the MRF Models.
Construction of EPR representation requires the measurement of Edge strength. Measuring of the Edge strength
is done using the Instantaneous Coefficient of Variation (ICOV). The basis of ICOV is the Watershed Algorithm
which is applied on the image to get the regions. Evaluation of the proposed method has been done using SAR
image which gets corrupted first by varying levels of Speckle Noise. The proposed method gives accuracy with
the combination of above mentioned models and also improves accuracy by 29% reduction in Computational
time.
Mari-Ann N. Meon, et.al, (2009) [2] list the brief study and exploration of SAR. In this paper [2] researchers
explored an automatic segmentation of syntheticaperture radar satellite images (SAR) satellite images of sea ice.
The investigation is based on a comparison of an automaticallysegmented SAR image and manual
classifications by iceservice analysts. Statistical ice properties are considered for segmenting SAR images into
classes. The number of classes is determined from available ground truth.Sea ice experts, aided by various in-
situ data, were able tolabel most of the segments from the automatic algorithm.They utilized the physical data of
the Polar metricfeatures which are used for classifying the algorithm, in order tofurther explore the class
labeling.
Phonsa G et al, (2014) [10] proposed a technique to resolve the object extraction problem. This technique helps
in object extraction on basis of area assessment size, pixel, enhancement and mining.
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International organization of Scientific Research 34 | P a g e
GuiGao, et.al, (2013) in their research paper [8] a CFAR method for the detection of ship in presence of high
resolution of SAR amplitude of dual polarization. In order to get better form of clutter ratio, a PMA detector has
been designed, thereby preventing any form of biasness for the ship due to SCR as it’s quite sensitive to clutter
ratio and the procedure thus helps to reduce the discrimination to a huge extent. Statistical model of PMA
detector has also been described using G0 distribution. This distribution is suitable for coping with the complex
backgrounds of sea.
B. Ramsay et al [4] proposed a design of a method of temporal segmentation for Multi Temporal segmentation
of sea ice to detecting the melting rate of multilayered sea ice. MODIS images has been generated for the
experimentation purposes, position of ice floes has been detected using microwave radiometer to determine the
position of ice floes with time and changing atmosphere. The procedure involves dividing the image into Floe
and the background. Feature extraction is done at the first place to extract the useful features followed by
marking of floes and shape constrained region growing is applied to detect to best shape. Region maps are
generated by post filtering and area of interest or ice floes is thus obtained using morphological operators on
piece of MODIS images. The advantage of this newly proposed approach is the availability of the area of the
image under study for the region of interest over the period of time. In this paper a study about [5] the study of
various feature extraction methods and is marked as an important research area in order to implement the
intelligent processing in more précised and effective manner. The best texture extraction method has been
determined based on the geostatistic principles and entropy concept. These are the two evaluating factors. The
proposed method is marked superior over the other pre existing approaches. Experiments has been performed on
medical data which is complex in nature due to the presence of discontinuities when it comes to X-rays or
magnetic resonance imaging and the piece of data is hard to segment and analyze.
ChristofRidder et.al [15] discusses the foreground and background estimations for image processing. For the
background estimations are done considering illuminations but does not present it as background, the author
proposed an approach using the CCD cameras of fixed length for making estimations. Back ground estimations
have been parallel, independent of pixel positions. Background estimation on smaller image resolution can also
be performed easily.
Simon J Julier and Jeffrey K. Uhlmann[16] describes the method of linear estimator that has been proposed
using the principle of sampled points which can parameterize mean and covariance and can easily work on the
nonlinear systems, Performance comparisons of the new approach has been done with the present Extended
Kalman Filter.
2 Proposed Methodology
SAR generated data is employed for mapping the ice. Among the various segmentation methods for
interpretation of such data, unsupervised approach is used. The data in the form of images is obtained from
RADARSAT 1 at the first place. But it does not provide accurate results. Thus development of various
automated algorithms reduced this hurdle to some extent but further enhancement in such techniques is further
required together with the source and RADARSAT 2 provided better outcomes in terms of considering factors
such as density and position. The given work is focused on analyzing the pixel data and the related
algorithms.[9] Study of region based algorithms and use will also lead to achieve the desired output and results.
Need to enhance SAR for RADAR1 imagery data. Now, RADARSAT 1 provides better results using the
concept of polarization in SAR and we can get more accurate results by enhancing it.
4. A Novel Technique for the better analysis of Ice Properties using Kalman Filtering
International organization of Scientific Research 35 | P a g e
Fig. 2.1Chart to show the context of proposed methodology
2.1 Algorithm:
INPUT: - INPUT IMAGE FOR SEA ICE DETECTION
OUTPUT: - VALUE OF IT,IC AND IV
Start ();
1.Input image and store in variable a;
2.[b c]=size(a);
3.Define initialize starting pixel and increment value of the pixels
4.If property of p(i,j)!=p(i+1,j+1)
5.Image will be segmented
6.Store value of IT, IV and IC
STOP ()
The existing algorithms SAR is compatible to RADARSAT1 and give accurate results to detect the ice
and for more accurate and efficient results of ice images we need to enhance the SAR algorithm. So, we need to
enhance the automated algorithms to capture better results. In proposed work we have used raster scan and
kalman filtering to get better and accurate results.
2.2 Experimental Results
Fig. 2.2.1Input Image
As shown in Figure 2.2.1, the image is input which contains ice and water. In this image technique of
morphological segmentation is applied to extract the image properties like Ice Thickness, Velocity and
Concentration.
5. A Novel Technique for the better analysis of Ice Properties using Kalman Filtering
International organization of Scientific Research 36 | P a g e
(a) (b) (c)
Fig. 2.2.2a) Thickness b) Velocity c) Concentration
In fig 2.2.2 the image is input which contains ice, water. In this image technique of morphological segmentation
is applied to extract the image properties like ice thickness, ice velocity and ice concentration.
Fig. 2.2.3Values in Text File
As shown in figure 2.2.3, the image is input which contains ice, water. In this image technique of morphological
segmentation is applied to extract the image properties like thickness, velocity and concentration. Final values of
Thickness, Velocity,and Concentration are defined and analyzed value is shown in text file.
Fig. 2.2.4Input Images
(a) (b) (c)
Fig. 2.2.5a) Ice Thickness b) Ice Concentration c) Ice Velocity
In this Figure 2.2.5, the image is input which contains ice, water. In this image technique of morphological
segmentation is applied to extract the image properties like ice thickness, ice velocity and ice concentration.
6. A Novel Technique for the better analysis of Ice Properties using Kalman Filtering
International organization of Scientific Research 37 | P a g e
Fig. 2.2.6 Final Values
As shown in Figure 2.2.6, the image is input which contains ice, water. In this image technique of
morphological segmentation is applied to extract the image properties like Ice Thickness, Velocity and
Concentration. The final values of ice concentration, ice velocity and ice thickness is defined and analyzed value
is shown in text file.
Table 2.2.1Results for observations
Images IT IC IV
Figure 2.3.2 (a),(b),(c) old=3.02
new=3.07
old=202
new=234
old=0.272
new=0.279
Figure 2.3.5 (a),(b),(c) old=2.54
new=2.59
old=147
new=153
old=0.226
new=0.236
IT: ICE THICKNESS
IC: ICE CONCENTRATION
IV: ICE VELOCITY
Table 2.2.1 represents the values generated for a set of five images namely, Image1 to Image 5. There is
increase in values for ice thickness, concentration and velocity after applying the proposed method.
II. CONCLUSION
The image segmentation is the technique in which the images are segmented for better analysis of the given
piece of data. In proposed work involves the segmentation of images of ice present in sea we are working on
ice sea segmentation. SAR is the algorithm being used for analyzing the properties of the ice sea images. Main
focus is on getting the ice properties in order to do the further analysis ad segmentation in an enhanced way. Ice
thickness, ice concentration and ice velocity are the important parameters being focused on to segment various
ice types as well. In this paper, an enhancement is being proposed in the SAR algorithm to do better analysis of
ice images and the ice types.
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