Depth Estimation Analysis Using Sum of Absolute Difference Algorithm

Stereo vision is one of the methods that can yield depth information of the scene. It uses stereo image pairs from two cameras to produce disparity maps that can be easily turn into depth maps. It is assumed that both the left and right channels of the multiview image sequence are coded using block or object-based methods. A dynamic programming algorithm is used to estimate a disparity field between each stereo image pair. Depth is then estimated and occlusions are optionally detected, based on the estimated disparity fields. Further, 2D and 3D motion compensation techniques are evaluated for the coding of sequences of depth or disparity maps. Reliability of depth maps and computational cost of algorithm is key issue for implementing real time robust applications. An algorithm for estimating reliable and accurate depth maps from stereoscopic image pairs is presented, which is based on correlation techniques for disparity estimation. By taking neighbouring disparity values into account, reliability and accuracy of the estimated disparity values are increased and the corona effect at disparity discontinuities is avoided. An interpolation of disparity values within segmented regions of homogeneous disparity enables the computation of dense depth maps by means of triangulation.