Optimization of Occlusion-Inducing Depth Pixels in 3-D Video Coding

The optimization of occlusion-inducing depth pixels in depth map coding has received little attention in the literature, since their associated texture pixels are occluded in the synthesized view and their effect on the synthesized view is considered negligible. However, the occlusion-inducing depth pixels still need to consume the bits to be transmitted, and will induce geometry distortion that inherently exists in the synthesized view. In this paper, we propose an efficient depth map coding scheme specifically for the occlusion-inducing depth pixels by using allowable depth distortions. Firstly, we formulate a problem of minimizing the overall geometry distortion in the occlusion subject to the bit rate constraint, for which the depth distortion is properly adjusted within the set of allowable depth distortions that introduce the same disparity error as the initial depth distortion. Then, we propose a dynamic programming solution to find the optimal depth distortion vector for the occlusion. The proposed algorithm can improve the coding efficiency without alteration of the occlusion order. Simulation results confirm the performance improvement compared to other existing algorithms

Bit allocation for multiview image compression using cubic synthesized view distortion model

"Texture-plus-depth" has become a popular coding format for multiview image compression, where a decoder can synthesize images at intermediate viewpoints using encoded texture and depth maps of closest captured view locations via depth-image-based rendering (DIBR). As in other resource-constrained scenarios, limited avail able bits must be optimally distributed among captured texture and depth maps to minimize the expected signal distortion at the decoder. A specific challenge of multiview image compression for DIBR is that the encoder must allocate bits without the knowledge of how many and which specific virtual views will be synthesized at the decoder for viewing. In this paper, we derive a cubic synthesized view distortion model to describe the visual quality of an interpolated view as a function of the view's location. Given the model, one can easily find the virtual view location between two coded views where the maximum synthesized distortion occurs. Using a multi view image codec based on shape-adaptive wavelet transform, we show how optimal bit allocation can be performed to minimize the maximum view synthesis distortion at any intermediate viewpoint. Our experimental results show that the optimal bit allocation can outperform a common uniform bit allocation scheme by up to 1.0dB in coding efficiency performance, while simultaneously being competitive to a state-of-the-art H.264 codec