Geometry transformation-based adaptive in-loop filter
Geometry transformation-based adaptive in-loop filter
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DOI：
10.1109/pcs.2016.7906346
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
M. Karczewicz;Li Zhang;Wei-Jung Chien;Xiang Li
中科院分区：
文献类型：
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作者：
M. Karczewicz;Li Zhang;Wei-Jung Chien;Xiang Li
近年来，用于图像/视频编码的自适应环路滤波器（ALF）因其在提高编码性能方面的能力而受到越来越多的关注。ALF的目标是通过使用基于维纳的自适应滤波器来最小化原始样本和解码样本之间的均方误差。图片中的样本被分类为多个类别，并且每个类别中的样本然后用其相关联的自适应滤波器进行滤波。滤波器系数可被信号化或继承以优化均方误差与开销之间的折衷。为了进一步提高ALF的性能，提出了一种基于几何变换的ALF（GALF）算法。该算法根据ALF前重构样本的梯度方向，对滤波器支持区域内的样本进行旋转、对角和垂直翻转等几何变换。随着几何变换的引入，支持更多的空间自适应，而无需过多地用信号通知滤波器系数。实验结果表明，GALF优于现有的ALF技术，它已被采用的JEM参考软件作为测试平台，为未来的视频编码技术的探索，在JVET。
Recently, adaptive in-loop filter (ALF) for image/video coding has attracted increasing attention by its proven capability in improving coding performance. ALF is aiming to minimize the mean square error between original samples and decoded samples by using Wiener-based adaptive filter. Samples in a picture are classified into multiple categories and the samples in each category are then filtered with their associated adaptive filter. The filter coefficients may be signaled or inherited to optimize the tradeoff between the mean square error and the overhead. In this paper, a Geometry transformation-based ALF (GALF) scheme is proposed to further improve the performance of ALF, which introduces geometric transformations, such as rotation, diagonal and vertical flip, to be applied to the samples in filter support region depending on the orientation of the gradient of the reconstructed samples before ALF. With the introduction of geometric transformations, more spatial adaptation is supported without excessive signaling of filter coefficients. The experimental results show that GALF outperforms the existing ALF techniques and it has been adopted by the JEM reference software used as the test platform for future video coding technology exploration in JVET.