Edge-preserving disparity estimation and disparity-compensated intermediate view reconstruction for stereo images

Abstract

A constrained disparity estimation method is proposed which uses a directional regularization technique to efficiently preserve edges for stereo image coding. The proposed method smoothes disparity vectors in smooth regions and preserves edges in object boundaries well, without creating an oversmoothing problem. The differential pulse code modulation (DPCM) technique for disparity map coding is used prior to entropy coding, in order to improve the overall coding efficiency. The proposed disparity estimation method can also be applied to intermediate view reconstruction. Intermediate views between a left image and a right image provide reality and natural motion parallax to multiviewers. Intermediate views are synthesized by appropriately exploiting an interpolation or an extrapolation technique according to the characteristics of each region after identifying the regions as occluded regions, normal regions, and regions having ambiguous disparities. The experimental results show that the proposed disparity estimation method gives close matches between a left image and a right image and improves coding efficiency. In addition, we can subjectively confirm that the application of our proposed intermediate view reconstruction method leads to satisfactory intermediate views from a stereo image pair.