Internal-video mode dependent directional transform - Li, Xiaolei; Lan, Cuiling; Shi, Yunhui; Ding, Wenpeng; Sun, Xiaoyan; Yin, Baocai (Visual Communications and Image Processing (VCIP), 2016, 2017)
As the projection of the real world, videos usually have many repeated patterns with similar structures cross regions, presenting strong non-local correlations. Moreover, different videos own different characteristics. Exploitation of the non-local correlations by off-line training of transforms has attracted considerable attention over the past years for compression. However, the samples used for training the transforms are usually collected from a predefined set of training videos to avoid the transmission of transform matrixes. There is no guarantee that the characteristics of those training videos and the corresponding transforms fit the current coding video very well. To address that, this paper proposes an internal-video mode dependent directional transform in HEVC for intra coding. In this scheme, for coding a video clip, based on different directions, a set of sample blocks is collected for each direction to train a Karhunen-Loeve transform at the video clip level. During encoding, the better transform between the proposed transform and original DCT/DST in HEVC is determined based on rate-distortion optimization. These transform matrixes are entropy coded to the bitstream. The proposed method can capture the statistical characteristics of the coded video clip and provide efficient transforms. Experimental results show that the proposed method achieves significant performance improvements in comparison with HEVC for intra coding, up to 13% BD-rate savings for the all intra configuration.
Best Student Paper