A low-rank matrix completion based intra prediction for H.264/AVC

Jin Wang, Yunhui Shi, Wenpeng Ding, Baocai Yin
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引用次数: 5

Abstract

Intra prediction plays an important role in reducing the spatial redundancy for intra frame encoding in H.264/AVC. In this paper, we propose a low-rank matrix completion based intra prediction to improve the prediction efficiency. According to the low-rank matrix completion theory, a low-rank matrix can be exactly recovered from quite limited samples with high probability under mild conditions. After moderate rearrangement and organization, image blocks can be represented as low-rank or approximately low-rank matrix. The intra prediction can then be formulated as a matrix completion problem, thus the unknown pixels can be inferred from limited samples with very high accuracy. Specifically, we novelly rearrange the encoded blocks similar to the current block to generate an observation matrix, from which the prediction can be obtained by solving a low-rank minimization problem. Experimental results demonstrate that the proposed scheme can achieve averagely 5.39% bit-rate saving for CIF sequences and 4.21% for QCIF sequences compared with standard H.264/AVC.
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基于H.264/AVC的低秩矩阵补全的帧内预测
帧内预测在减少H.264/AVC帧内编码的空间冗余方面起着重要的作用。为了提高预测效率,本文提出了一种基于低秩矩阵补全的图像内预测方法。根据低秩矩阵补全理论,在较温和的条件下,低秩矩阵可以在相当有限的样本中以高概率精确地恢复出来。经过适度的重排和组织,图像块可以表示为低秩或近似低秩矩阵。然后可以将内部预测公式化为矩阵补全问题,因此可以从有限的样本中以非常高的精度推断未知像素。具体而言,我们将与当前块相似的编码块进行新颖的重新排列,生成观测矩阵,通过求解低秩最小化问题得到预测。实验结果表明,与标准H.264/AVC相比,该方案可实现CIF序列的平均比特率节约5.39%,QCIF序列的平均比特率节约4.21%。
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