New data formats that include both video and the corresponding depth maps, such as multiview plus depth
(MVD), enable new video applications in which intermediate video views (virtual views) can be generated using
the transmitted/stored video views (reference views) and the corresponding depth maps as inputs. We propose a
depth map coding method based on a new distortion measurement by deriving relationships between distortions
in coded depth map and rendered view. In our experiments we use a codec based on H.264/AVC tools, where the
rate-distortion (RD) optimization for depth encoding makes use of the new distortion metric. Our experimental
results show the efficiency of the proposed method, with coding gains of up to 1.6 dB in interpolated frame
quality as compared to encoding the depth maps using the same coding tools but applying RD optimization
based on conventional distortion metrics.
This paper presents a technique for coding high dynamic range videos. The proposed coding scheme is scalable, such that both standard dynamic range and high dynamic range representations of a video can be extracted from one bit stream. A localized inverse tone mapping method is proposed for efficient inter-layer prediction, which applies a scaling factor and an offset to each macroblock, per color channel. The scaling factors and offsets are predicted from neighboring macroblocks, and then the differences are entropy coded. The proposed inter-layer prediction technique is independent of the forward tone mapping method and is able to cover a wide range of bit-depths and various color spaces. Simulations are performed based on H.264/AVC SVC common software and core experiment conditions. Results show the effectiveness of the proposed method.
The chrominance subsampling has been widely used for the image and video compression. However, this can cause color distortion and image quality degradation. We developed a new sampling method in which the residual image after intra or inter prediction is subsampled instead of the original image subsampling. Since the residual image contains fewer information than the original image does generally, the information loss is reduced when the residual image is downsampled. Also the upsampling procedure is much less sensitive to the filtering methods selected as demonstrated in the experimental results. So we can apply a simple filtering to reduce the complexity. The experimental results show the effectiveness of the proposed sampling method. This sampling method can be further improved by applying adaptively according to the statistics of each block, and can be applied to the RGB image directly without color conversion.