{"title":"小波图像阈值去噪研究","authors":"Chenggang Zhen, Yingmei Su","doi":"10.1109/ICFPEE.2010.8","DOIUrl":null,"url":null,"abstract":"The purpose of image denoising is to restore the original image from the observed noisy image, under the conditions of meeting the minimum mean-square error criteria. In this paper, it summarized the basic principles of the wavelet threshold de-noising and various factors that affect the denoising performace in a complete de-noising algorithms, and analyzed several commonly used threshold de-noising methods and experiment with the Lena image. It provided the basis of selection and improvement for the actual image processing de-noising method.","PeriodicalId":412111,"journal":{"name":"2010 International Conference on Future Power and Energy Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Research on Wavelet Image Threshold De-noising\",\"authors\":\"Chenggang Zhen, Yingmei Su\",\"doi\":\"10.1109/ICFPEE.2010.8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of image denoising is to restore the original image from the observed noisy image, under the conditions of meeting the minimum mean-square error criteria. In this paper, it summarized the basic principles of the wavelet threshold de-noising and various factors that affect the denoising performace in a complete de-noising algorithms, and analyzed several commonly used threshold de-noising methods and experiment with the Lena image. It provided the basis of selection and improvement for the actual image processing de-noising method.\",\"PeriodicalId\":412111,\"journal\":{\"name\":\"2010 International Conference on Future Power and Energy Engineering\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Future Power and Energy Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFPEE.2010.8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Future Power and Energy Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPEE.2010.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The purpose of image denoising is to restore the original image from the observed noisy image, under the conditions of meeting the minimum mean-square error criteria. In this paper, it summarized the basic principles of the wavelet threshold de-noising and various factors that affect the denoising performace in a complete de-noising algorithms, and analyzed several commonly used threshold de-noising methods and experiment with the Lena image. It provided the basis of selection and improvement for the actual image processing de-noising method.
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