{"title":"基于神经网络的自适应多尺度图像去噪","authors":"M. Srinivasan, S. Annadurai","doi":"10.1109/SPCOM.2004.1458373","DOIUrl":null,"url":null,"abstract":"An image is often corrupted by additive Gaussian noise during its acquisition and transmission. Denoising has to be performed on these images to retain the signal and to suppress the noise. Denoising can be performed by various methods like thresholding, filtering etc. But these methods did not consider the local space scale information of the image. Here a new type of neural network is constructed for noise reduction, where the space scale information of the image is considered. This method gives a good numerical results and also better visual effects.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive multiscale image denoising using neural networks\",\"authors\":\"M. Srinivasan, S. Annadurai\",\"doi\":\"10.1109/SPCOM.2004.1458373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An image is often corrupted by additive Gaussian noise during its acquisition and transmission. Denoising has to be performed on these images to retain the signal and to suppress the noise. Denoising can be performed by various methods like thresholding, filtering etc. But these methods did not consider the local space scale information of the image. Here a new type of neural network is constructed for noise reduction, where the space scale information of the image is considered. This method gives a good numerical results and also better visual effects.\",\"PeriodicalId\":424981,\"journal\":{\"name\":\"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPCOM.2004.1458373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPCOM.2004.1458373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive multiscale image denoising using neural networks
An image is often corrupted by additive Gaussian noise during its acquisition and transmission. Denoising has to be performed on these images to retain the signal and to suppress the noise. Denoising can be performed by various methods like thresholding, filtering etc. But these methods did not consider the local space scale information of the image. Here a new type of neural network is constructed for noise reduction, where the space scale information of the image is considered. This method gives a good numerical results and also better visual effects.