{"id":151446,"date":"2000-06-01T00:00:00","date_gmt":"2000-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/three-dimensional-shape-adaptive-discrete-wavelet-transforms-for-efficient-object-based-video-coding\/"},"modified":"2018-10-16T20:47:00","modified_gmt":"2018-10-17T03:47:00","slug":"three-dimensional-shape-adaptive-discrete-wavelet-transforms-for-efficient-object-based-video-coding","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/three-dimensional-shape-adaptive-discrete-wavelet-transforms-for-efficient-object-based-video-coding\/","title":{"rendered":"Three-dimensional shape-adaptive discrete wavelet transforms for efficient object-based video coding"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In this paper, we present an object-based coding scheme using three-dimensional shape-adaptive discrete wavelet transforms (SA-DWT). Rather than straightforward extension of 2D SA-DWT, a novel way to handle the temporal wavelet transform using a motion model is proposed to achieve higher coding efficiency. Corresponding to this transform scheme, we use a 3D entropy coding algorithm called Motion-based Embedded Subband Coding with Optimized Truncation (ESCOT) to code the wavelet coefficients. Results show that ESCOT can achieve comparable coding performance with the state-of-the-art MPEG-4 verification model (VM) 13.0 while having the scalability and flexibility of the bitstream in low bit-rate object-based video coding. And in relative higher bit-rate, our coding approach outperforms MPEG-4 VM 13.0 by about 2.5dB.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we present an object-based coding scheme using three-dimensional shape-adaptive discrete wavelet transforms (SA-DWT). Rather than straightforward extension of 2D SA-DWT, a novel way to handle the temporal wavelet transform using a motion model is proposed to achieve higher coding efficiency. Corresponding to this transform scheme, we use a 3D entropy coding algorithm [&hellip;]<\/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":"","msr-author-ordering":[{"type":"user_nicename","value":"jzxu"},{"type":"user_nicename","value":"spli"},{"type":"user_nicename","value":"yzhang"}],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"\u00a9 2000 IEEE. Personal use of this material is permitted. However, permission to reprint\/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the 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