Zhuoyuan Chen, Jiangtao Wen, Shiqiang Yang, Yuxing Han, J. Villasenor
{"title":"Image Compression Using the DCT and Noiselets: A New Algorithm and Its Rate Distortion Performance","authors":"Zhuoyuan Chen, Jiangtao Wen, Shiqiang Yang, Yuxing Han, J. Villasenor","doi":"10.1109/DCC.2010.62","DOIUrl":null,"url":null,"abstract":"We describe an image coding algorithm combining the DCT and noiselet information. The algorithm first transmits DCT information sufficient to reproduce a \"low-quality\" version of the image at the decoder. This image is then used both at the decoder and encoder to create a mutually known list of locations of likely significant noiselet coefficients. The coefficient values themselves are then transmitted to the decoder differentially, by subtracting, at the encoder, the low-quality image from the original image, obtaining the noiselet values and subjecting them to quantization and entropy coding. There remain significant opportunities for further work combining CS-inspired information theoretic techniques with the rate-distortion considerations that are critical in practical image communications.","PeriodicalId":299459,"journal":{"name":"2010 Data Compression Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2010.62","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We describe an image coding algorithm combining the DCT and noiselet information. The algorithm first transmits DCT information sufficient to reproduce a "low-quality" version of the image at the decoder. This image is then used both at the decoder and encoder to create a mutually known list of locations of likely significant noiselet coefficients. The coefficient values themselves are then transmitted to the decoder differentially, by subtracting, at the encoder, the low-quality image from the original image, obtaining the noiselet values and subjecting them to quantization and entropy coding. There remain significant opportunities for further work combining CS-inspired information theoretic techniques with the rate-distortion considerations that are critical in practical image communications.