Disparity estimation with hierarchical block correlation for stereoscopic image coding

Abstract

Disparity compensation is widely used to remove the spatial redundancies in stereoscopic image coding. In this paper, we present a disparity estimation algorithm called hierarchical block correlation, which is a hybrid of the hierarchical estimation approach with the correlation matching criterion. To assess the performance of the proposed algorithm, a coding error-based measure is used. The proposed algorithm is compared with two conventional block matching algorithms. The simulation results indicate that the proposed algorithm reduces disparity vector entropy by 10% to 30% and gives comparable or smaller coding errors. Furthermore, the proposed algorithm is superior with regard to the reliability of disparity vectors, and thus can give better image quality for applications such as low-bit-rate coding and image interpolation.