{"title":"Improved quality of experience of reconstructed H.264/AVC encoded video sequences through robust pixel domain error detection","authors":"R. Farrugia, C. J. Debono","doi":"10.1109/MMSP.2008.4665108","DOIUrl":null,"url":null,"abstract":"The transmission of H.264/AVC encoded sequences over noisy wireless channels generally adopt the error detection capabilities of the transport protocol to identify and discard corrupted slices. All the macroblocks (MBs) within each corrupted slice are then concealed. This paper presents an algorithm that does not discard the corrupted slices but tries to detect those MBs which provide major visual artefacts and then conceal only these MBs. Results show that the proposed solution, based on a set of image-level features and two support vector machines (SVMs), manages to detect 94.6% of those artefacts. Gains in peak signal-to-noise ratios (PSNR) of up to 5.74 dB have been obtained when compared to the standard H.264/AVC decoder.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE 10th Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2008.4665108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The transmission of H.264/AVC encoded sequences over noisy wireless channels generally adopt the error detection capabilities of the transport protocol to identify and discard corrupted slices. All the macroblocks (MBs) within each corrupted slice are then concealed. This paper presents an algorithm that does not discard the corrupted slices but tries to detect those MBs which provide major visual artefacts and then conceal only these MBs. Results show that the proposed solution, based on a set of image-level features and two support vector machines (SVMs), manages to detect 94.6% of those artefacts. Gains in peak signal-to-noise ratios (PSNR) of up to 5.74 dB have been obtained when compared to the standard H.264/AVC decoder.