M. Ghazel, R. Ward, R. Abugharbieh, E. Vrscay, G. H. Freeman
{"title":"同时分形图像去噪与插值","authors":"M. Ghazel, R. Ward, R. Abugharbieh, E. Vrscay, G. H. Freeman","doi":"10.1109/PACRIM.2005.1517350","DOIUrl":null,"url":null,"abstract":"In this paper, a simple and effective fractal-based simultaneous image denoising and interpolation scheme is proposed and implemented. The denoising is performed during the fractal encoding process while the interpolation is performed during the decoding process. The fractal-based image denoising involves predicting the fractal code of the original noiseless image from the statistics of the noisy observation. This fractal code can then be used to generate a fractally denoised estimate of the original image. The fractal interpolation can be easily achieved during the decoding process by iterating the predicted fractal code on a suitably sized blank initial image seed. The cycle spinning algorithm can also be incorporated in the proposed fractal joint denoising and resizing scheme in order to reduce some of the artifacts and enhance the visual quality of the fractally denoised and resized estimates.","PeriodicalId":346880,"journal":{"name":"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Simultaneous fractal image denoising and interpolation\",\"authors\":\"M. Ghazel, R. Ward, R. Abugharbieh, E. Vrscay, G. H. Freeman\",\"doi\":\"10.1109/PACRIM.2005.1517350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a simple and effective fractal-based simultaneous image denoising and interpolation scheme is proposed and implemented. The denoising is performed during the fractal encoding process while the interpolation is performed during the decoding process. The fractal-based image denoising involves predicting the fractal code of the original noiseless image from the statistics of the noisy observation. This fractal code can then be used to generate a fractally denoised estimate of the original image. The fractal interpolation can be easily achieved during the decoding process by iterating the predicted fractal code on a suitably sized blank initial image seed. The cycle spinning algorithm can also be incorporated in the proposed fractal joint denoising and resizing scheme in order to reduce some of the artifacts and enhance the visual quality of the fractally denoised and resized estimates.\",\"PeriodicalId\":346880,\"journal\":{\"name\":\"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM.2005.1517350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.2005.1517350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simultaneous fractal image denoising and interpolation
In this paper, a simple and effective fractal-based simultaneous image denoising and interpolation scheme is proposed and implemented. The denoising is performed during the fractal encoding process while the interpolation is performed during the decoding process. The fractal-based image denoising involves predicting the fractal code of the original noiseless image from the statistics of the noisy observation. This fractal code can then be used to generate a fractally denoised estimate of the original image. The fractal interpolation can be easily achieved during the decoding process by iterating the predicted fractal code on a suitably sized blank initial image seed. The cycle spinning algorithm can also be incorporated in the proposed fractal joint denoising and resizing scheme in order to reduce some of the artifacts and enhance the visual quality of the fractally denoised and resized estimates.