{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T06:41:05Z","timestamp":1742798465807},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Unc. Fuzz. Knowl. Based Syst."],"published-print":{"date-parts":[[1997,12]]},"abstract":"<jats:p> Differential pulse code modulation (DPCM) algorithms are widely used to compress gray-scale pictures. A critical element in a DPCM algorithm is the accurate prediction of the pixel gray-levels in the input picture. The switched predictors used in modern DPCM algorithms are generally accurate when the input picture is free of noise. However, even small amounts of noise in the input picture will cause a substantial reduction in prediction accuracy and in turn a reduction in compression efficiency. In this paper we describe a novel fuzzy rule-based predictor for use in a lossless DPCM algorithm. For noisy pictures, the accuracy of the new predictor is consistently higher than the accuracy of standard switched predictors. <\/jats:p>","DOI":"10.1142\/s0218488597000506","type":"journal-article","created":{"date-parts":[[2003,10,22]],"date-time":"2003-10-22T01:39:04Z","timestamp":1066786744000},"page":"689-699","source":"Crossref","is-referenced-by-count":3,"title":["A Fuzzy Switched DPCM Predictor for Lossless Compression of Noisy Images"],"prefix":"10.1142","volume":"05","author":[{"given":"H. B.","family":"Mitchell","sequence":"first","affiliation":[{"name":"Signal Processing and Computing Department, Elta Electronics Industries Ltd., Ashdod, Israel"}]},{"given":"D. D.","family":"Estrakh","sequence":"additional","affiliation":[{"name":"Signal Processing and Computing Department, Elta Electronics Industries Ltd., Ashdod, Israel"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218488597000506","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T03:04:21Z","timestamp":1565147061000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218488597000506"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1997,12]]},"references-count":0,"journal-issue":{"issue":"06","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1997,12]]}},"alternative-id":["10.1142\/S0218488597000506"],"URL":"https:\/\/doi.org\/10.1142\/s0218488597000506","relation":{},"ISSN":["0218-4885","1793-6411"],"issn-type":[{"value":"0218-4885","type":"print"},{"value":"1793-6411","type":"electronic"}],"subject":[],"published":{"date-parts":[[1997,12]]}}}