7.7  Conclusions

In this chapter, we have presented a joint depth-texture bit-allocation algorithm for the compression of multi-view images. To perform a joint bit-allocation optimization, we have proposed to combine both the depth and texture R-D curves into a single unified R-D surface. We have empirically verified that the R-D surface presents smooth monotonic properties so that fast optimization algorithms can be employed. A hierarchical search for estimating the optimal quantization parameters, which is similar to the Tree-Step Search for motion estimation, was implemented. Experimental results have revealed that the performance is comparable to a full-search parameter optimization. Because the algorithm features low computational complexity, the described joint bit-allocation optimization technique can be readily integrated into the N-depth/N-texture multi-view encoder, which is currently investigated within the FTV framework of MPEG.

The original problem statement mentioned at the beginning of this chapter formulated the R-D optimization as a function of the coding of texture and depth signals and the applied rendering. In the experiments, we have employed a specific rendering algorithm to come to feasible results. However, the total optimization should encompass an optimization of the rendering algorithm as well. This was beyond the scope of this thesis.

The concept as posed in this chapter does not only apply to 3D-TV transmission, but also to other cases where geometry and depth is encoded, such as in computer graphics. In such a case, the rendering function would have a different behavior and may be different specifications, but it would play an equally important role in the problem statement and optimization. Similarly, the concept can also be applied to different coding algorithms involving the compression of geometry and texture signals.