{"id":32,"date":"2017-08-21T12:04:46","date_gmt":"2017-08-21T16:04:46","guid":{"rendered":"https:\/\/sites.bu.edu\/cheng-group\/?page_id=32"},"modified":"2025-09-24T13:31:20","modified_gmt":"2025-09-24T17:31:20","slug":"resources","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/cheng-group\/resources\/","title":{"rendered":"Resources"},"content":{"rendered":"<h2 class=\"default-headline\">Group github repository<\/h2>\n<p><span>Cheng group code repository <a href=\"https:\/\/github.com\/buchenglab\">[Link]<\/a>.<\/span><\/p>\n<h2 class=\"default-headline\">Mutilvariate Curve Resolution<\/h2>\n<p><span>The\u00a0<\/span><a href=\"https:\/\/engineering.purdue.edu\/ChengGroup\/resources\/mcr\/mcr-labview-code\">Labview based code<\/a><span>\u00a0helps reading hyperspectral image data and performs MCR analysis.<\/span><\/p>\n<h2 class=\"default-headline\">Denoising Hyperspectral Images<\/h2>\n<p>The<span>\u00a0<\/span><a href=\"https:\/\/engineering.purdue.edu\/ChengGroup\/resources\/denoising\/spectral-total-variation\">spectral total variation<\/a><span>\u00a0<\/span>(STV) denoising algorithm is a new denoising algorithm for hyperspectral images that estimates different noise levels across the spectral axis from observed data.<\/p>\n<p>The code can also be downloaded from Matlab FileExchange:<\/p>\n<p><a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/52478-the-spectral-total-variation-denoising-algorithm\">http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/52478-the-spectral-total-variation-denoising-algorithm<\/a><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Group github repository Cheng group code repository [Link]. Mutilvariate Curve Resolution The\u00a0Labview based code\u00a0helps reading hyperspectral image data and performs MCR analysis. Denoising Hyperspectral Images The\u00a0spectral total variation\u00a0(STV) denoising algorithm is a new denoising algorithm for hyperspectral images that estimates different noise levels across the spectral axis from observed data. The code can also be [&hellip;]<\/p>\n","protected":false},"author":13793,"featured_media":0,"parent":0,"menu_order":9,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/pages\/32"}],"collection":[{"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/users\/13793"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/comments?post=32"}],"version-history":[{"count":10,"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/pages\/32\/revisions"}],"predecessor-version":[{"id":2327,"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/pages\/32\/revisions\/2327"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/cheng-group\/wp-json\/wp\/v2\/media?parent=32"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}