Visual stereo matching combined with intuitive transition of pixel values

The objective of stereo matching is to find the corresponding pixels from similar two or more images. However, it is difficult problem to get precise and consistent disparity under a variety of real world situations. In other words, the color values of stereo images are easily influenced by radiometric factors such as illumination direction, illumination color, and camera exposure. Therefore, conventional stereo matching methods can have low performances under radiometric conditions. In this paper, we propose a novel stereo matching approach that is robust in controlling various radiometric variations such as local and global radiometric variations. We designed a hybrid stereo matching approach using transition of pixel values and data fitting. Transition of pixel values is utilized for the coarse stereo matching stage, and polynomial curve fitting is used for the fine stereo matching stage. Experimental results show that the proposed method has better performances compared to the stereo matching algorithms of comparison group under severely different radiometric conditions between stereo images. Consequentially, we demonstrate that the proposed method is less sensitive to various radiometric variations, and shows an outstanding performance in computational complexity.

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