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3 articles for “Discrete Shearlet Transform”

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Research ArticleOpen accessPhrase in the titleDiscrete Shearlet Transform and Lempel-Ziv Welch Coding for Lossless Fingerprint Image CompressionNahidah A. Kadim, Shawkat K. Guirguis, Hend A. ElsayedImage compression is a crucial task in image processing and in the process of sending and receiving files. There is a need for effective techniques for image compression as the raw images require large amounts of disk space to defect during transportation and storage operations. The most important objective of image compression is to decrease the redundancy of the image … …Journal of Computer Science, Vol. 20, Issue 5 · 5 Mar 2024 · 5,485 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA NOVELTY APPROACH OF SPATIAL CO-OCCURRENCE AND DISCRETE SHEARLET TRANSFORM BASED TEXTURE CLASSIFICATION USING LPBOOSTING CLASSIFIERC. Vivek, S. AudithanRecently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial co-occurrence with discrete shearlet transformation through the LPboosting classification. It can be considered as a frame through … …Journal of Computer Science, Vol. 10, Issue 5 · 11 Jan 2014 · 6,602 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMass Classification in Digital Mammograms based on Discrete Shearlet TransformJ. Amjath Ali, J. JanetThe most significant health problem in the world is breast cancer and early detection is the key to predict it. Mammography is the most reliable method to diagnose breast cancer at the earliest. The classification of the two most findings in the digital mammograms, micro calcifications and mass are valuable for early detection. Since, the appearance of the masses are … …Journal of Computer Science, Vol. 9, Issue 6 · 1 Jun 2013 · 6,549 accessesView PDFCite