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Open Access Pixel-Based Adaptive Normalized Cross Correlation for Illumination Invariant Stereo Matching

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Stereo matching methods estimate a disparity value of the object as depth information. In general, most stereo matching methods are tested under ideal radiometric conditions. However, those ideal conditions cannot exist in real life. Adaptive normalized cross correlation (ANCC) is a method that is robust to radiometric variation. It estimates significantly accurate disparity values in the illumination variant condition. However, it has a high complexity problem in the cost computation because of the block matching-based method and the bilateral filtering process. In this paper, we propose a pixel-based ANCC using hue and gradient information to improve the computation complexity problem. The results show that the cost computation time is reduced even though error rates corresponding to the exposure and illumination changes have larger variations than those of the ANCC result.

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Keywords: DISPARITY MAP; GLOBAL MEAN VALUE; HUE TRANSFORM; STEREO MATCHING

Document Type: Research Article

Publication date: January 1, 2017

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