{"title":"自然图像的轮廓去噪","authors":"A. Bin Mansoor, S.A. Khan","doi":"10.1109/ICALIP.2008.4590267","DOIUrl":null,"url":null,"abstract":"The paper investigates the image denoising utilizing a new discrete transform, contourlet transform through thresholding technique for natural images. We investigate the new transform with varied amount of noise for three sigma thresholding on a block of four natural images. Signal to noise ratio and visual judgement are made to assess the denoised images. The method displays improved signal to noise ratio for noisy images, but with observable artifacts.","PeriodicalId":175885,"journal":{"name":"2008 International Conference on Audio, Language and Image Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Contoulet denoising of natural images\",\"authors\":\"A. Bin Mansoor, S.A. Khan\",\"doi\":\"10.1109/ICALIP.2008.4590267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper investigates the image denoising utilizing a new discrete transform, contourlet transform through thresholding technique for natural images. We investigate the new transform with varied amount of noise for three sigma thresholding on a block of four natural images. Signal to noise ratio and visual judgement are made to assess the denoised images. The method displays improved signal to noise ratio for noisy images, but with observable artifacts.\",\"PeriodicalId\":175885,\"journal\":{\"name\":\"2008 International Conference on Audio, Language and Image Processing\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Audio, Language and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALIP.2008.4590267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Audio, Language and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALIP.2008.4590267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper investigates the image denoising utilizing a new discrete transform, contourlet transform through thresholding technique for natural images. We investigate the new transform with varied amount of noise for three sigma thresholding on a block of four natural images. Signal to noise ratio and visual judgement are made to assess the denoised images. The method displays improved signal to noise ratio for noisy images, but with observable artifacts.
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