Depth Map Compression Based on Platelet Coding and Quadratic Curve Fitting

In this paper, we propose an efficient depth data compression scheme for depth images. Our proposed scheme is a platelet based coding method using quadtree decomposition, Lagrangian optimization function, and quadratic curve fitting algorithm. In this scheme, quadtree decomposition is used to divide a depth map into blocks with one or two homogeneous regions; Lagrangian optimization is employed to minimize the distortion as well as to keep relative high compression ratio within each sub-block; Four quadratic curve fitting models are designed for the objects' contours in order to keep the edges' position more precisely after compression. The experimental results show that our proposed method can achieve compression ratio comparable to the other known platelet based method. Besides, the objects' contours are kept better compared to the other method.