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In this paper, diverse procedures are used under block-based classification to distinguish the compound image segments. The segmentation process starts with separation of the entire image into blocks by spare decomposition technique in smooth blocks and non smooth blocks. Gray wolf-optimization based FCM (fuzzy C-means) algorithm is employed to segment background, text, graphics, images and overlap, which are then individually compressed using adaptive Huffman coding, embedded zero wavelet and H.264 coding techniques. Exploratory outcomes demonstrate that the proposed conspire expands compression ratio, enhances image quality and additionally limits computational complexity. The proposed method is implemented on the working platform of MATLAB.<\/jats:p>","DOI":"10.1515\/jisys-2017-0360","type":"journal-article","created":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T18:16:23Z","timestamp":1524680183000},"page":"515-528","source":"Crossref","is-referenced-by-count":0,"title":["Sparse Decomposition Technique for Segmentation and Compression of Compound Images"],"prefix":"10.1515","volume":"29","author":[{"given":"V.N.","family":"Manju","sequence":"first","affiliation":[{"name":"Faculty of Computer Science and Engineering , Sathyabama Institute of Science and Technology , Chennai , India"}]},{"given":"A.","family":"Lenin Fred","sequence":"additional","affiliation":[{"name":"Mar Ephraem College of Engineering and Technology , Marthandam, Tamil Nadu , India"}]}],"member":"374","published-online":{"date-parts":[[2018,4,25]]},"reference":[{"key":"2025120523293259979_j_jisys-2017-0360_ref_001","doi-asserted-by":"crossref","unstructured":"S. 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