A Stereo Matching Algorithm under Outdoor Unideal Illumination Condition

To solve the problem of poor stereo matching effect caused by unideal outdoor illumination conditions and low-texture or low-contrast areas, a new stereo matching algorithm is proposed based on edge-map guided segmentation method under HSL (Hue-Saturation-Luminosity) color space. Different from traditional pixel-intensity based measurement under RGB color space, an HSL-color-space based pixel dissimilarity measurement equation is used in the proposed algorithm to calculate matching costs, and then image region segmentation and stereo matching are completed based on the edge detection results of the left and right input images. A series of image sets with different illumination conditions and significant low-texture areas are used for comparison between the proposed algorithm and the existing methods. Experiment results show that the proposed algorithm can achieve ideal disparity maps, be robust for images with unideal illumination and low-texture areas, and run in near real-time.