Entropy based Log Chromaticity Projection for Real-time Stereo Matching

Most of the existing stereo matching algorithms will assume a similar corresponding color values between stereo images. In the real scenario, these color values are effected by several radiometric factors such as illumination direction, illumination color, camera parameters, etc, which results in different color values between the corresponding points. Hence, applying the stereo algorithm directly on the raw color values is not appropriate for the real-time environment. This paper proposes an entropy minimization based log chromaticity projection for stereo image, thereby extracting the invariant image, which is independent of illumination and color. The developed invariant image is the perfect measure for finding the similarity between the corresponding points. Normalized cross correlation based similarity measure is applied on the generated invariant image and the obtained disparity outperforms some of the local and global stereo algorithms.