{"title":"A projection on Convex Sets super-resolution algorithm using wavelet transform","authors":"Guo Lei, He Zhiming","doi":"10.1109/ICOSP.2008.4697306","DOIUrl":null,"url":null,"abstract":"Projection on convex sets (POCS) is an algorithm which produces high-resolution image from a set of low-resolution images, but doesnpsilat perform very well on the reconstruction of high frequency information and depressing noise. In this paper, wavelet transform is utilized to extract high frequency hidden information and depress the noise in the low resolution images based on POCS, thus the detailed information of images and SNR are better than the results of normal POCS. The results of simulation confirm that the method in this paper is more effective than POCS algorithm.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 9th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2008.4697306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Projection on convex sets (POCS) is an algorithm which produces high-resolution image from a set of low-resolution images, but doesnpsilat perform very well on the reconstruction of high frequency information and depressing noise. In this paper, wavelet transform is utilized to extract high frequency hidden information and depress the noise in the low resolution images based on POCS, thus the detailed information of images and SNR are better than the results of normal POCS. The results of simulation confirm that the method in this paper is more effective than POCS algorithm.