Reducing Bitrate and Increasing the Quality of Inter Frame by Avoiding Quantization Errors in Stationary Blocks

Xuan-Tu Tran, Ngoc-Sinh Nguyen, Duy-Hieu Bui, Minh-Trien Pham, Hung K. Nguyen, C. Pham
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Abstract

In image compression and video coding, quantization error helps to reduce the amount of information of the high frequency components. However, in temporal prediction the quantization error contributes its value as noise in the total residual information. Therefore, the residual signal of the inter-picture prediction is greater than the expected one and always differs zero value even input video contains only homogeneous frames. In this paper, we reveal negative effects of quantization errors in inter prediction and propose a video encoding scheme which is able to avoid side effects of quantization errors in the stationary parts. We propose to implement a motion detection algorithm as the first stage of video encoding to separate the video into two parts: motion and static. The motion information allows us to force residual data of non-changed part to zero and keep the residual signal of motion regularly. Beside, we design block-based filters which improve motion results and filter those results fit into block encode size well. Fixed residual data of static information permits us to pre-calculate its quantized coefficient and create a bypass encoding path for it. Experimental results with the JPEG compression (MJPEG-DPCM) showed that the proposed method produces lower bitrate than the conventional MJPEG-DPCM at the same quantization parameter and a lower computational complexity. Received on 13 September 2019; accepted on 11 December 2019; published on 17 January 2020
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通过避免固定块中的量化错误来降低比特率并提高帧间质量
在图像压缩和视频编码中,量化误差有助于减少高频分量的信息量。然而,在时间预测中,量化误差在总残差信息中以噪声的形式贡献其值。因此,图像间预测的残差信号大于预期的残差信号,即使输入视频只有均匀帧,残差信号也始终为零。本文揭示了量化误差对内部预测的负面影响,并提出了一种能够避免平稳部分量化误差副作用的视频编码方案。我们提出实现一种运动检测算法作为视频编码的第一阶段,将视频分为运动和静态两部分。运动信息使我们能够将未变化部分的残差数据强制为零,并有规律地保持运动的残差信号。此外,我们设计了基于块的滤波器,改善了运动结果,并对符合块编码大小的结果进行了很好的滤波。静态信息的固定残差数据允许我们预先计算其量化系数,并为其创建一个旁路编码路径。用JPEG压缩(MJPEG-DPCM)进行的实验结果表明,在相同的量化参数下,该方法比传统的MJPEG-DPCM产生更低的比特率和更低的计算复杂度。2019年9月13日收到;2019年12月11日接受;于2020年1月17日发布
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来源期刊
CiteScore
4.00
自引率
0.00%
发文量
15
审稿时长
10 weeks
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