{"title":"基于MP的图像稀疏分解新方法","authors":"Yingyun Yang, Dongxin Shi, Ke Sun, Qin Zhang","doi":"10.1109/CIIP.2009.4937882","DOIUrl":null,"url":null,"abstract":"One of main problems in image sparse decomposition is the contradiction between the quality of the image and the algorithm's speed. To overcome this key problem, a new fast algorithm is presented. At first the number of atoms is decreased by making use of the atom energy property; then this algorithm converts very time-consuming inner product calculations in sparse decomposition into correlations that are fast done by FFT. Experimental results show that the performance of the proposed algorithm is effective.","PeriodicalId":349149,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Image Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new approach to image sparse decomposition based on MP\",\"authors\":\"Yingyun Yang, Dongxin Shi, Ke Sun, Qin Zhang\",\"doi\":\"10.1109/CIIP.2009.4937882\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of main problems in image sparse decomposition is the contradiction between the quality of the image and the algorithm's speed. To overcome this key problem, a new fast algorithm is presented. At first the number of atoms is decreased by making use of the atom energy property; then this algorithm converts very time-consuming inner product calculations in sparse decomposition into correlations that are fast done by FFT. Experimental results show that the performance of the proposed algorithm is effective.\",\"PeriodicalId\":349149,\"journal\":{\"name\":\"2009 IEEE Symposium on Computational Intelligence for Image Processing\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Computational Intelligence for Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIIP.2009.4937882\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Computational Intelligence for Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIIP.2009.4937882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new approach to image sparse decomposition based on MP
One of main problems in image sparse decomposition is the contradiction between the quality of the image and the algorithm's speed. To overcome this key problem, a new fast algorithm is presented. At first the number of atoms is decreased by making use of the atom energy property; then this algorithm converts very time-consuming inner product calculations in sparse decomposition into correlations that are fast done by FFT. Experimental results show that the performance of the proposed algorithm is effective.