{"id":273471,"date":"2004-03-23T09:00:23","date_gmt":"2004-03-23T17:00:23","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=273471"},"modified":"2018-10-16T21:11:16","modified_gmt":"2018-10-17T04:11:16","slug":"a-foregroundbackground-separation-algorithm-for-image-compression","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-foregroundbackground-separation-algorithm-for-image-compression\/","title":{"rendered":"A Foreground\/Background Separation Algorithm for Image Compression"},"content":{"rendered":"
Many bitmap documents are composed by the superposition of layers with pictures and text. These documents do not compress well using image compression algorithms such as JPEG-2000, because text introduces sharp edges on top of the smooth surfaces typically found in natural images. Similarly, compression algorithms for text facsimiles, such as JBIG2, are not suited for color or gray level images. We propose the SLIm system for separating text and line drawing from background images, in order to compress both more effectively. This approach differ from previous ones such as DjVu, Tiff-FX, and MRC, by being extremely simple and fast, while yielding close to state-of-the-art compression performance. We present results that show that the SLIm compression performance is attractive for many applications.<\/p>\n","protected":false},"excerpt":{"rendered":"
Many bitmap documents are composed by the superposition of layers with pictures and text. These documents do not compress well using image compression algorithms such as JPEG-2000, because text introduces sharp edges on top of the smooth surfaces typically found in natural images. Similarly, compression algorithms for text facsimiles, such as JBIG2, are not suited […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13561,13551],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-273471","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-research-area-graphics-and-multimedia","msr-locale-en_us"],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_edition":"IEEE Data Compression 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