{"title":"Hyperspectral Imagery Denoising Using Minimum Noise Fraction and Video Non-Local Bayes Algorithms","authors":"Guangyi Chen, A. Krzyżak, S. Qian","doi":"10.1080/07038992.2022.2116307","DOIUrl":null,"url":null,"abstract":"Abstract Hyperspectral imagery (HSI) denoising is a popular research topic in remote sensing. In this paper, we propose a novel method for HSI denoising by performing Minimum Noise Fraction (MNF) to the original HSI data cube, thresholding the noisy output bands with the Video Non-Local Bayes (VNLB) algorithm, and then conducting the inverse MNF transform to obtain the denoised data cube. Our experiments demonstrate that the proposed method usually achieves the best denoising results among several existing denoising methods for two HSI data cubes. In addition, it is much faster for HSI denoising than the VNLB algorithm which was originally developed for video denoising.","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":"48 1","pages":"694 - 701"},"PeriodicalIF":2.0000,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/07038992.2022.2116307","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Hyperspectral imagery (HSI) denoising is a popular research topic in remote sensing. In this paper, we propose a novel method for HSI denoising by performing Minimum Noise Fraction (MNF) to the original HSI data cube, thresholding the noisy output bands with the Video Non-Local Bayes (VNLB) algorithm, and then conducting the inverse MNF transform to obtain the denoised data cube. Our experiments demonstrate that the proposed method usually achieves the best denoising results among several existing denoising methods for two HSI data cubes. In addition, it is much faster for HSI denoising than the VNLB algorithm which was originally developed for video denoising.
期刊介绍：
Canadian Journal of Remote Sensing / Journal canadien de télédétection is a publication of the Canadian Aeronautics and Space Institute (CASI) and the official journal of the Canadian Remote Sensing Society (CRSS-SCT).
Canadian Journal of Remote Sensing provides a forum for the publication of scientific research and review articles. The journal publishes topics including sensor and algorithm development, image processing techniques and advances focused on a wide range of remote sensing applications including, but not restricted to; forestry and agriculture, ecology, hydrology and water resources, oceans and ice, geology, urban, atmosphere, and environmental science. Articles can cover local to global scales and can be directly relevant to the Canadian, or equally important, the international community. The international editorial board provides expertise in a wide range of remote sensing theory and applications.
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