{"title":"In-loop filter for H.264/AVC","authors":"G. Poornima, S. Kumar, S. Ramachandran","doi":"10.1109/RTEICT.2017.8256992","DOIUrl":null,"url":null,"abstract":"In H.264/AVC, block — based transformation, quantization, scaling, inverse scaling and inverse transformation are applied for the reconstruction of future reference frame in the encoder to diminish spatial and also temporal redundancies. With block-based coding technique, at block boundaries discontinuities are created which are known as blocking Distortions. These are predominant at block boundaries and this affects image during the reconstruction process and is one the most infuriating blocking distortion in video and image compressions. These blocking Distortions deteriorate the image or video quality. To overcome this problem, and to recover the frame of image or video, quite a few algorithms have available. In this paper we proposed and implemented In-Loop filtering algorithm to smoothen the Distortions of compressed image. The performance of the reconstructed image after the in-loop filtering is measured by the conventional parameters such as prediction gain and Peak Signal to Noise Ratio.","PeriodicalId":342831,"journal":{"name":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTEICT.2017.8256992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

In H.264/AVC, block — based transformation, quantization, scaling, inverse scaling and inverse transformation are applied for the reconstruction of future reference frame in the encoder to diminish spatial and also temporal redundancies. With block-based coding technique, at block boundaries discontinuities are created which are known as blocking Distortions. These are predominant at block boundaries and this affects image during the reconstruction process and is one the most infuriating blocking distortion in video and image compressions. These blocking Distortions deteriorate the image or video quality. To overcome this problem, and to recover the frame of image or video, quite a few algorithms have available. In this paper we proposed and implemented In-Loop filtering algorithm to smoothen the Distortions of compressed image. The performance of the reconstructed image after the in-loop filtering is measured by the conventional parameters such as prediction gain and Peak Signal to Noise Ratio.
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用于 H.264/AVC 的内环滤波器
在 H.264/AVC 中,基于块的变换、量化、缩放、反缩放和反变换用于在编码器中重建未来参考帧,以减少空间和时间冗余。采用基于块的编码技术时,在块边界会产生不连续性,即所谓的块失真。这些不连续性主要出现在区块边界,在重建过程中会影响图像,是视频和图像压缩中最令人恼火的阻塞失真之一。这些阻塞失真会降低图像或视频的质量。为了克服这一问题,并恢复图像或视频的帧,有许多算法可用。在本文中,我们提出并实施了环内滤波算法来平滑压缩图像的失真。通过预测增益和峰值信噪比等传统参数来衡量环内滤波后重建图像的性能。
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