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108 results for “Images Noise”

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Research ArticleOpen accessIn the abstractFish Classification Based on Robust Features Extraction From Color Signature Using Back-Propagation ClassifierMutasem Khalil Alsmadi, Khairuddin Bin Omar, Shahrul Azman Mohd NoahProblem statement: Image recognition was a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,641 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Performance of Backpropagation Neural Network Algorithm for Image Compression/Decompression SystemOmaima N.A. AL-AllafProblem statement: The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality. Artificial neural networks are becoming attractive in image processing where high computational performance and parallel architectures are required. … …Journal of Computer Science, Vol. 6, Issue 11 · 26 Oct 2010 · 8,374 accessesView PDFCite
Research ArticleOpen accessIn the abstractSuccessive Image Interpolation Using Lifting Scheme ApproachRohini S. Asamwar, Kishor Bhurchandi, A. S. GandhiProblem statement: Fast and accurate interpolation and resizing of images and video frames is a much sought after research area in multimedia applications. The more accurate schemes are computationally expensive and require more time for execution. We proposed here Discrete Wavelet Transform (DWT) using lifting scheme as an accurate and computationally inexpensive interpolation technique for image resizing. Approach: In this … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 7,577 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpeckle Suppression of Radar Images Using Normalized ConvolutionA. K. Helmy, G. S. El-TaweelProblem statement: Synthetic Aperture Radar (SAR) images are becoming more widely used in remote sensing applications. SAR uses microwave radiation to illuminate the earth's surface. The coherent microwave illumination, however, suffers from fading effects result in generating a multiplicative speckle noise that corrupts SAR images. Approach: Through this study, scheme to reduce speckles was proposed, it was designed to accomplish … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 7,264 accessesView PDFCite
Research ArticleOpen accessIn the abstractFish Recognition Based on Robust Features Extraction from Size and Shape Measurements Using Neural NetworkMutasem Khalil Alsmadi, Khairuddin Bin Omar, Shahrul Azman Noah, Ibrahim AlmarashdehProblem statement: Image recognition is a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 9,308 accessesView PDFCite
Research ArticleOpen accessIn the abstractModified Curvelet Thresholding Algorithm for Image DenoisingAl-Dahoud Ali, Preety D. Swami, J. SinghaiProblem statement: This study introduced an adaptive thresholding method for removing additive white Gaussian noise from digital images. Approach: Curvelet transform employed in the proposed scheme provides sparse decomposition as compared to the wavelet transform methods which being nongeometrical lack sparsity and fail to show optimal rate of convergence. Results: Different behaviors of curvelet transform maxima of image and noise … …Journal of Computer Science, Vol. 6, Issue 1 · 31 Jan 2010 · 7,261 accessesView PDFCite
Research ArticleOpen accessIn the abstractSlantlet Transform for Multispectral Image FusionAdnan Hadi M. Al-Helali, Hamza A. Ali, Buthainah Al-Dulaimi et al.Problem statement: Image fusion is a process by which multispectral and panchromatic images, or some of their features, are combined together to form a high spatial/high spectral resolutions image. The successful fusion of images acquired from different modalities or instruments is a great importance issue in remote sensing applications. Approach: A new method of image fusion was introduced. It was … …Journal of Computer Science, Vol. 5, Issue 4 · 30 Apr 2009 · 7,729 accessesView PDFCite
Research ArticleOpen accessIn the abstractError Free Iterative Morphological Decomposition Algorithm for Shape RepresentationV. Vijaya Kumar, A. Srikrishna, G. Hemantha KumarProblem statement: A generalized skeleton transform allows a shape to be represented as a collection of modestly overlapped octagonal shape parts. One problem with several generalized Morphological skeleton transforms is that they generate noise after decomposition. The noise rate may not be effective for ordinary images; however this effect will be more when applied on printed or handwritten characters. Approach: … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 7,524 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdapting the LMF Temporal Splining Procedure From Serial to MPI/Linux ClustersSajia Akhter, Ipshita Sarkar, Kazi G. Rabbany et al.Remote Sensing (RS) provides images over large areas such as provincial or country level. During the last 20 years, it plays a vital role for developing many complex applications. However, RS image includes data noises due to influence of haze or cloud especially in the rainy season. It is thus necessary to remove the noise to recover the real ground … …Journal of Computer Science, Vol. 3, Issue 3 · 31 Mar 2007 · 7,467 accessesView PDFCite
Research NotesOpen accessIn the abstractReal Time Density-Based Clustering (RTDBC) Algorithm for Big DataDr. B. Ravi PrasadDensity Based Spatial Clustering of Applications with Noise (DBSCAN), a well-known Density-Based Clustering Algorithm is a advanced data clustering method with various applications in numerous fields like Satellites images, X-ray crystallography, Anomaly Detection in Temperature Data. But its run time R(n2) complexity draws a major challenge. In this research paper, we propose a new unique algorithm called Real Time Density … …Journal of Computer Science, Vol. 13, Issue 10 · 15 Aug 2017 · 7,304 accessesView PDFCite