Multiview video compression with 1-D transforms

• The characteristics of disparity-compensated prediction residuals are analyzed.
• Analysis revealed that many of its local regions can have 1-D signal characteristics.
• It was proposed to use 1-D transforms in multiview video coding.
• Experiments are conducted to show the gains achievable from using these transforms.
• Results indicated that overall compression efficiency increases.

Many alternative transforms have been developed recently for improved compression of images, intra prediction residuals or motion-compensated prediction residuals. In this paper, we propose alternative transforms for multiview video coding. We analyze the spatial characteristics of disparity-compensated prediction residuals, and the analysis results show that many regions have 1-D signal characteristics, similar to previous findings for motion-compensated prediction residuals. Signals with such characteristics can be transformed more efficiently with transforms adapted to these characteristics and we propose to use 1-D transforms in the compression of disparity-compensated prediction residuals in multiview video coding. To show the compression gains achievable from using these transforms, we modify the reference software (JMVC) of the multiview video coding amendment to H.264/AVC so that each residual block can be transformed either with a 1-D transform or with the conventional 2-D Discrete Cosine Transform. Experimental results show that coding gains ranging from about 1–15% of Bjontegaard-Delta bitrate savings can be achieved.