Transforms for the disparity-compensated prediction residuals

Previous research indicates that motion-compensated prediction residuals can have 1-D (dimensional) structures in many regions and that 1-D directional transforms can compress such regions more efficiently than 2-D Discrete Cosine Transform (DCT). In this paper, 1-D transforms are also used for the compression of disparity-compensated prediction residuals based on analysis results, which indicate that disparity-compensated prediction residuals also have 1-D structures in many regions. To show the achievable compression efficiency gains from using these transforms, JMVC reference software is modified so that each residual block can be transformed either with a 1-D transform or 2-D DCT. Experimental results indicate that the overall compression efficiency increases.