{"title":"QR迭代子空间识别及其在图像去噪中的应用","authors":"Chanzi Liu, Qingchun Chen","doi":"10.1109/ICIG.2011.176","DOIUrl":null,"url":null,"abstract":"The foundation of compressed sensing (CS) is the sparse representation of signals. Over-complete dictionaries could be utilized to map signals into their sparse representation over the dictionary. And iterative subspace identification (ISI) is an effective algorithm to determine the over-complete dictionary from signal samples. In this paper, the QR decomposition is proposed to be employed in the ISI scheme so as to obtain the adaptive over-complete dictionary. It is shown that the QR-ISI outperforms the ISI in terms of the recovered PSNR. Finally, the QR-ISI method could be applied to image denoising. Experiment results are presented to show that the QR-ISI offers a feasible method for image denoising with reasonable performance.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"QR Iterative Subspace Identification and Its Application in Image Denoising\",\"authors\":\"Chanzi Liu, Qingchun Chen\",\"doi\":\"10.1109/ICIG.2011.176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The foundation of compressed sensing (CS) is the sparse representation of signals. Over-complete dictionaries could be utilized to map signals into their sparse representation over the dictionary. And iterative subspace identification (ISI) is an effective algorithm to determine the over-complete dictionary from signal samples. In this paper, the QR decomposition is proposed to be employed in the ISI scheme so as to obtain the adaptive over-complete dictionary. It is shown that the QR-ISI outperforms the ISI in terms of the recovered PSNR. Finally, the QR-ISI method could be applied to image denoising. Experiment results are presented to show that the QR-ISI offers a feasible method for image denoising with reasonable performance.\",\"PeriodicalId\":277974,\"journal\":{\"name\":\"2011 Sixth International Conference on Image and Graphics\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Sixth International Conference on Image and Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIG.2011.176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Image and Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIG.2011.176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
QR Iterative Subspace Identification and Its Application in Image Denoising
The foundation of compressed sensing (CS) is the sparse representation of signals. Over-complete dictionaries could be utilized to map signals into their sparse representation over the dictionary. And iterative subspace identification (ISI) is an effective algorithm to determine the over-complete dictionary from signal samples. In this paper, the QR decomposition is proposed to be employed in the ISI scheme so as to obtain the adaptive over-complete dictionary. It is shown that the QR-ISI outperforms the ISI in terms of the recovered PSNR. Finally, the QR-ISI method could be applied to image denoising. Experiment results are presented to show that the QR-ISI offers a feasible method for image denoising with reasonable performance.
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