Abstract
This paper deals with the block-based disparity map estimation of a stereoscopic image. While most existing algorithms estimate this map by minimizing a dissimilarity metric, the proposed optimization algorithm aims at minimizing the rate-distortion compromise using the disparity map yielded by the traditional block matching algorithm as an initial reference map. The developed algorithm analyzes the performance impact of the permutation of each disparity of the reference map with all possible disparities. The retained disparity is one that improves the joint rate-distortion metric. This process is repeated as long as improvements are observed. Moreover, a particular attention is given to the updating process of the joint metric so that the algorithm computational cost is not affected. Simulation results clearly show that our approach achieves better performance than the traditional block matching algorithm in terms of rate-distortion compromise.
Published Version
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