SAD Stereo Matching Algorithm

This article introduces the SAD (Sum of Absolute Differences) stereo matching algorithm, a fundamental technique for computing disparity maps that enhances our understanding of stereoscopic images. The algorithm operates on standard benchmark images from computer vision databases, which require no pre-rectification before processing. At its core, SAD compares corresponding pixel blocks between left and right stereo images by calculating the absolute intensity differences within a defined search window. The implementation typically involves sliding a comparison window across scan lines while tracking the minimum SAD value to determine optimal pixel correspondence. Through this method, we consistently generate accurate disparity maps suitable for subsequent image analysis. The algorithm demonstrates high stability and precision in disparity calculation, making it widely adopted in computer vision applications and robotics for depth perception tasks. Key implementation aspects include window size optimization, boundary handling, and computational efficiency improvements through techniques like integral image precomputation.