{"title":"An accelerated method to predict the quality of decoded images in fractal image coding","authors":"Qiang Wang, Sheng Bi, Guohua Jin","doi":"10.1109/CISP.2015.7407873","DOIUrl":null,"url":null,"abstract":"With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the quality of decoded images. By making use of the ACER in the encoding process, the quality of decoded images can be predicted without fractal decoding. In order to shorten the prediction process further, an accelerated version of the prediction method is proposed. By theoretical derivations and analyses, a low limit of accumulated collage error (LLPACE) is introduced which provides an effective way to evaluate the percentage of total collage error accounted by the accumulated collage error (ACE). Experiments show that for either basic fractal coding or other three fast fractal coding methods, the accelerated prediction method can provide satisfying performance and reduce about one third of total computations in the encoding process.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2015.7407873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the quality of decoded images. By making use of the ACER in the encoding process, the quality of decoded images can be predicted without fractal decoding. In order to shorten the prediction process further, an accelerated version of the prediction method is proposed. By theoretical derivations and analyses, a low limit of accumulated collage error (LLPACE) is introduced which provides an effective way to evaluate the percentage of total collage error accounted by the accumulated collage error (ACE). Experiments show that for either basic fractal coding or other three fast fractal coding methods, the accelerated prediction method can provide satisfying performance and reduce about one third of total computations in the encoding process.