Chapter 7
Joint Depth-Texture Bit Allocation

“Joint undertakings stand a better chance when they benefit both sides, – Clavius added the axiom that the whole is equal to the sum of its parts.”


Euripides, Greek tragedians. In this chapter, we propose a novel joint depth-texture bit-allocation algorithm for the joint compression of texture and depth images. The described algorithm combines the depth and texture Rate-Distortion (R-D) curves to obtain a single R-D surface that allows the optimization of the joint bit-allocation problem in relation to the obtained rendering quality. We subsequently discuss a fast hierarchical optimization algorithm that exploits the smooth monotonic properties of the R-D surface. The hierarchical optimization algorithm employs an orthogonal search pattern, so that the number of image-compression iterations for measuring quality is minimized. Experimental results show an estimated gain of 1 dB compared to a compression performed without joint bit-allocation optimization. Besides this advantage, our joint model can be readily integrated into an N-depth/N-texture multi-view encoder, as it yields the optimal compression setting with a limited computation effort.

 7.1 Introduction
 7.2 Joint depth/texture bit allocation
  7.2.1 Formulation of the joint bit-allocation problem
  7.2.2 R-D surface analysis
 7.3 Hierarchical search optimization
 7.4 Relationship between the depth and texture bit rate
 7.5 Applications of the joint bit-allocation framework
 7.6 Experimental results
 7.7 Conclusions