VLSI processor for reliable stereo matching based on adaptive window-size selection

Stereo vision is a well known method to acquire 3D information. One important problem in stereo vision is to establish reliable correspondence between images. Another problem is that the correspondence search is time-consuming. This paper presents a reliable stereo-matching algorithm and a new parallel VLSI processor architecture for stereo matching. One commonly-used method to establish correspondence between images is the SAD (sum of absolute differences) method. A window size is iteratively enlarged to select as small a window for each pixel as possible that can avoid ambiguity based on uniqueness of a minimum of an SAD graph. This process is called a global search. Next, the estimate of the corresponding pixel obtained by the global search is iteratively refined by shrinking the window size. To avoid ambiguity with a small window size, the correspondence estimate obtained by the global search is efficiently used. The proposed algorithm has regular data flow based on iterations of SAD computation so that it is suitable for parallel processing.