{"title":"纠错视频编码端到端失真的块大小自适应变换域估计","authors":"Bohan Li, Tejaswi Nanjundaswamy, K. Rose","doi":"10.1109/ICIP.2016.7532727","DOIUrl":null,"url":null,"abstract":"The accuracy of end-to-end distortion (EED) estimation is crucial to achieving effective error resilient video coding. An established solution, the recursive optimal per-pixel estimate (ROPE), does so by tracking the first and second moments of decoder-reconstructed pixels. An alternative estimation approach, the spectral coefficient-wise optimal recursive estimate (SCORE), tracks instead moments of decoder-reconstructed transform coefficients, which enables accounting for transform domain operations. However, the SCORE formulation relies on a fixed transform block size, which is incompatible with recent standards. This paper proposes a non-trivial generalization of the SCORE framework which, in particular, accounts for arbitrary block size combinations involving the current and reference block partitions. This seemingly intractable objective is achieved by a two-step approach: i) Given the fixed block size moments of a reference frame, estimate moments of transform coefficients for the codec-selected current block partition; ii) Convert the current results to transform coefficient moments corresponding to a regular fixed block size grid, to facilitate EED estimation for the next frame. Experimental results first demonstrate the accuracy of the proposed estimate in conjunction with transform domain temporal prediction. Then the estimate is leveraged to optimize the coding mode and yields considerable gains in rate-distortion performance.","PeriodicalId":6521,"journal":{"name":"2016 IEEE International Conference on Image Processing (ICIP)","volume":"7 1","pages":"2092-2096"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Block-size adaptive transform domain estimation of end-to-end distortion for error-resilient video coding\",\"authors\":\"Bohan Li, Tejaswi Nanjundaswamy, K. Rose\",\"doi\":\"10.1109/ICIP.2016.7532727\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The accuracy of end-to-end distortion (EED) estimation is crucial to achieving effective error resilient video coding. An established solution, the recursive optimal per-pixel estimate (ROPE), does so by tracking the first and second moments of decoder-reconstructed pixels. An alternative estimation approach, the spectral coefficient-wise optimal recursive estimate (SCORE), tracks instead moments of decoder-reconstructed transform coefficients, which enables accounting for transform domain operations. However, the SCORE formulation relies on a fixed transform block size, which is incompatible with recent standards. This paper proposes a non-trivial generalization of the SCORE framework which, in particular, accounts for arbitrary block size combinations involving the current and reference block partitions. This seemingly intractable objective is achieved by a two-step approach: i) Given the fixed block size moments of a reference frame, estimate moments of transform coefficients for the codec-selected current block partition; ii) Convert the current results to transform coefficient moments corresponding to a regular fixed block size grid, to facilitate EED estimation for the next frame. Experimental results first demonstrate the accuracy of the proposed estimate in conjunction with transform domain temporal prediction. Then the estimate is leveraged to optimize the coding mode and yields considerable gains in rate-distortion performance.\",\"PeriodicalId\":6521,\"journal\":{\"name\":\"2016 IEEE International Conference on Image Processing (ICIP)\",\"volume\":\"7 1\",\"pages\":\"2092-2096\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Image Processing (ICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2016.7532727\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2016.7532727","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Block-size adaptive transform domain estimation of end-to-end distortion for error-resilient video coding
The accuracy of end-to-end distortion (EED) estimation is crucial to achieving effective error resilient video coding. An established solution, the recursive optimal per-pixel estimate (ROPE), does so by tracking the first and second moments of decoder-reconstructed pixels. An alternative estimation approach, the spectral coefficient-wise optimal recursive estimate (SCORE), tracks instead moments of decoder-reconstructed transform coefficients, which enables accounting for transform domain operations. However, the SCORE formulation relies on a fixed transform block size, which is incompatible with recent standards. This paper proposes a non-trivial generalization of the SCORE framework which, in particular, accounts for arbitrary block size combinations involving the current and reference block partitions. This seemingly intractable objective is achieved by a two-step approach: i) Given the fixed block size moments of a reference frame, estimate moments of transform coefficients for the codec-selected current block partition; ii) Convert the current results to transform coefficient moments corresponding to a regular fixed block size grid, to facilitate EED estimation for the next frame. Experimental results first demonstrate the accuracy of the proposed estimate in conjunction with transform domain temporal prediction. Then the estimate is leveraged to optimize the coding mode and yields considerable gains in rate-distortion performance.