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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:使用基于自适应加权最小二乘的预测器改进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)及其最新扩展的高效视频编码(H.265 / HEVC)是具有定向和平面帧内预测器的当前工业视频编码标准。两种标准的帧内预测方案都由定向预测器控制。基于普通最小二乘(OLS)的自适应预测器在边缘像素周围优越,而无需明确考虑边缘的方向。在基于OLS的预测器中,局部区域中的每个像素贡献相等的权重以估计预测参数。我们观察到,由于噪声以及每个相邻像素的因果关系之间存在不同的相关性,这并不成立。为解决此问题,我们提出了一种基于自适应加权最小二乘(AWLS)的预测器,该预测器为相邻像素分配不同的权重以反映其相对贡献。实验结果表明,对于定向图像,该方法优于基于OLS的帧内预测,​​对于其他测试图像和视频,该方法的边缘性得到了改善。

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