{"title":"提出了一种基于WBCT和分块阈值的无线衰落信道人脸图像编码新方案","authors":"M. Owjimehr, M. Yazdi, A. Z. Asli","doi":"10.1109/IRANIANMVIP.2010.5941168","DOIUrl":null,"url":null,"abstract":"Transmitting the face image data through wireless fading channels have been widely used for face recognition and automatic surveillance applications and many techniques can be used to do that. However, due to the noise and wireless fading channels, the perfect recovery cannot be achieved. So there are needs to use efficient techniques for image recovery and denoising. The wavelet and contourlet transforms along with some denoising schemes such as Hard thresholding to estimate the true coefficients from noisy ones have been already used. In this paper, we propose to use Wavelet-Based Contourlet Transform (WBCT) comprised with Block thresholding to more efficiently denoise and recovery transmitted face images. The simulation results show that for general face images the WBCT is quite competitive to the contourlet and wavelet transforms in the SNR sense and in visual aspects.","PeriodicalId":350778,"journal":{"name":"2010 6th Iranian Conference on Machine Vision and Image Processing","volume":"201 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A new scheme of face image encoding through wireless fading channels using WBCT and Block thresholding\",\"authors\":\"M. Owjimehr, M. Yazdi, A. Z. Asli\",\"doi\":\"10.1109/IRANIANMVIP.2010.5941168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Transmitting the face image data through wireless fading channels have been widely used for face recognition and automatic surveillance applications and many techniques can be used to do that. However, due to the noise and wireless fading channels, the perfect recovery cannot be achieved. So there are needs to use efficient techniques for image recovery and denoising. The wavelet and contourlet transforms along with some denoising schemes such as Hard thresholding to estimate the true coefficients from noisy ones have been already used. In this paper, we propose to use Wavelet-Based Contourlet Transform (WBCT) comprised with Block thresholding to more efficiently denoise and recovery transmitted face images. The simulation results show that for general face images the WBCT is quite competitive to the contourlet and wavelet transforms in the SNR sense and in visual aspects.\",\"PeriodicalId\":350778,\"journal\":{\"name\":\"2010 6th Iranian Conference on Machine Vision and Image Processing\",\"volume\":\"201 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 6th Iranian Conference on Machine Vision and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRANIANMVIP.2010.5941168\",\"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 6th Iranian Conference on Machine Vision and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRANIANMVIP.2010.5941168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new scheme of face image encoding through wireless fading channels using WBCT and Block thresholding
Transmitting the face image data through wireless fading channels have been widely used for face recognition and automatic surveillance applications and many techniques can be used to do that. However, due to the noise and wireless fading channels, the perfect recovery cannot be achieved. So there are needs to use efficient techniques for image recovery and denoising. The wavelet and contourlet transforms along with some denoising schemes such as Hard thresholding to estimate the true coefficients from noisy ones have been already used. In this paper, we propose to use Wavelet-Based Contourlet Transform (WBCT) comprised with Block thresholding to more efficiently denoise and recovery transmitted face images. The simulation results show that for general face images the WBCT is quite competitive to the contourlet and wavelet transforms in the SNR sense and in visual aspects.