帧内微块复制的屏幕图像编码算法

针对现有的帧内块复制（IBC）算法不能很好地适应屏幕图像具有各种不同大小和形状样图的问题，为了进一步提高屏幕图像的编码效率，提出了一种帧内微块复制（IMBC）算法。该算法首先将当前编码单元（CU）划分成L个微块。然后以每个微块作为最小的匹配和复制单元，采用匹配微块组选择算法，在参考像素集合R中找到与当前微块最匹配的“参考微块”。用L个位移矢量（DV）来表示“参考微块”所在位置与当前CU所在位置的位移关系。最后，对L个位移矢量应用预测算法以消除位移矢量之间的相关性后进行熵编码。对于屏幕图像标准测试数据集合中的视频序列，IMBC算法与IBC算法相比，在编码复杂度增加较低的前提下，在全帧内（AI）、随机接入（RA）、低延迟（LB）三种编码配置中，有损BD-rate降低率分别达3.4%、2.9%、2.6%，无损Bit-rate降低率分别达9.5%、5.2%、5.1%，能有效提高屏幕图像的编码效率。

Intra mini-block copy algorithm for screen content coding

Concerning the problem that existing Intra Bock Copy (IBC) algorithm is not well suitable to the screen content with a variety of different sizes and shapes of patterns, an Intra Mini-Block Copy (IMBC) algorithm was proposed to further improve coding efficiency of the screen content. Firstly, the Coding Unit (CU) was divided into a set of L mini-blocks. Secondly, each mini-block was taken as the smallest matching and replication unit, the reference mini-block which matched the mini-block best was found in the reference set R by a mini-block matching optimal selection strategy. And the location of the reference mini-block and its location in the current CU were specified by L Displacement Vectors (DVs). Finally, a prediction algorithm was firstly applied to the L DVs for eliminating the correlation between DVs before entropy encoding. Compared with the IBC algorithm, for the High Efficiency Video Coding (HEVC), Screen Content Coding (SCC) test sequences, IMBC achieved the BD-rate reduction up to 3.4%, 2.9%, 2.6% for All Intra (AI), Random Access (RA) and Low-delay B (LB) configurations in lossy coding respectively, and the Bit-rate saving up to 9.5%, 5.2%, 5.1% for AI, RA, LB configurations in lossless coding respectively. The experimental results show that IMBC algorithm can effectively improve the coding efficiency of screen image at very low additional encoding and decoding complexity.