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Improving the Intra-prediction of H.264 and H.265 Video Coding Standards Using Adaptive Weighted Least Squares Based Predictor

机译:基于自适应加权最小二乘预测的预测器,提高H.264和H.265视频编码标准的帧内预测

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Advanced Video Coding (H.264/AVC) and its recent extension High Efficiency Video Coding (H.265/HEVC) are the current industrial video coding standards that have directional and planar intra-predictors. The intra-prediction scheme of both standards is dominated by directional predictors. Ordinary least squares (OLS) based adaptive predictor is superior around edge pixels without considering the direction of an edge explicitly. In OLS based predictor, each pixel in the local area contributes equal weight to estimate prediction parameters. We observed that this does not hold true due to noise and the existence of different correlations between the causal context of each neighboring pixel. To address this problem, we proposed an adaptive weighted least squares (AWLS) based predictor that assigns different weights to neighboring pixels to reflect its relative contribution. Experimental results show that the proposed method outperforms the OLS based intraprediction for directional images and marginal improvements are obtained for other tested images and videos.
机译:高级视频编码(H.264 / AVC)和其最近扩展的高效视频编码(H.265 / HEVC)是目前工业视频编码具有方向性和平面内预测标准。这两种标准的帧内预测方案是通过定向预测支配。普通最小二乘(OLS)基于自适应预测器是优越的周围边缘像素,而不考虑的边缘的方向明确。在基于OLS预测,在本地区域中的每个像素有助于相等的权重来估计预测参数。我们观察到,这不成立,由于噪声和每个相邻像素之间的因果语境之间的不同相关性的存在。为了解决这个问题,我们提出了一种自适应加权最小二乘(AWLS)基于预测器不同的权重,以相邻像素受让人,以反映其相对贡献。实验结果表明,所提出的方法优于其它测试的图像和视频获得用于定向图像和边缘的改进的基于帧内预测的OLS。

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