{"title":"压缩感知均衡算法研究","authors":"J. Ren, T. Tang","doi":"10.1109/SIPROCESS.2016.7888248","DOIUrl":null,"url":null,"abstract":"Digital image is generally used in various fields in real life. Massive photos of rapid acquisition become an important content of the signal processing. Compressed sensing (CS) theory undersampling technology provides a new image transmission storage as well as new thought. Algorithm which obtains the image may appear halation, fuzzy, and other problems aroused by many sorts of problems. In order to meet the demand of more advanced image evaluation standard, homogenization treatment is required. This paper is aimed to improve the image quality combined with the compressed perception theory and is mainly based on the equalization algorithm.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on compressed sensing equalization algorithms\",\"authors\":\"J. Ren, T. Tang\",\"doi\":\"10.1109/SIPROCESS.2016.7888248\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital image is generally used in various fields in real life. Massive photos of rapid acquisition become an important content of the signal processing. Compressed sensing (CS) theory undersampling technology provides a new image transmission storage as well as new thought. Algorithm which obtains the image may appear halation, fuzzy, and other problems aroused by many sorts of problems. In order to meet the demand of more advanced image evaluation standard, homogenization treatment is required. This paper is aimed to improve the image quality combined with the compressed perception theory and is mainly based on the equalization algorithm.\",\"PeriodicalId\":142802,\"journal\":{\"name\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"volume\":\"156 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIPROCESS.2016.7888248\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPROCESS.2016.7888248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on compressed sensing equalization algorithms
Digital image is generally used in various fields in real life. Massive photos of rapid acquisition become an important content of the signal processing. Compressed sensing (CS) theory undersampling technology provides a new image transmission storage as well as new thought. Algorithm which obtains the image may appear halation, fuzzy, and other problems aroused by many sorts of problems. In order to meet the demand of more advanced image evaluation standard, homogenization treatment is required. This paper is aimed to improve the image quality combined with the compressed perception theory and is mainly based on the equalization algorithm.
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