Depth Estimation Using Stereo Medical Imaging

Abstract

Depth estimation has importance in many applications such as robot navigation, 3D movies, human-computer interfaces, medical depth detection imaging, etc. Different maps are generated using stereo communication algorithms. In-depth information is displayed using a contrast map. Generally, depth is estimated by Sum of absolute difference (SAD), Semi Global Block Matching (SGBM), and Normalized Cross Correlation algorithms. We have implemented these algorithms in the Python language. These algorithms generate a map of variance with intelligent block matching and slope limits. In experimentation, the Semi Global Block algorithm shows better results.