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Consequently, the theory of data compression becomes more significant for reducing data redundancy in order to allow more transfer and storage of data. In this context, this paper addresses the problem of lossy image compression. Indeed, this new proposed method is based on the block singular value decomposition (SVD) power method that overcomes the disadvantages of MATLAB\u2019s SVD function in order to make a lossy image compression. The experimental results show that the proposed algorithm has better compression performance compared with the existing compression algorithms that use MATLAB\u2019s SVD function. In addition, the proposed approach is simple in terms of implementation and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.<\/jats:p>","DOI":"10.1515\/jisys-2018-0034","type":"journal-article","created":{"date-parts":[[2019,4,2]],"date-time":"2019-04-02T05:01:38Z","timestamp":1554181298000},"page":"1345-1359","source":"Crossref","is-referenced-by-count":2,"title":["Image Compression Based on Block SVD Power Method"],"prefix":"10.1515","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4260-6898","authenticated-orcid":false,"given":"Khalid El","family":"Asnaoui","sequence":"first","affiliation":[{"name":"Complex Systems Engineering and Human Systems , Mohammed VI Polytechnic University , Lot 660, Hay Moulay Rachid, Ben Guerir 43150 , Morocco"}]}],"member":"374","published-online":{"date-parts":[[2019,4,2]]},"reference":[{"key":"2025120523362727208_j_jisys-2018-0034_ref_001","unstructured":"M. A. 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