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Anisotropic reaction-diffusion stereo algorithm

机译:各向异性反应扩散立体算法

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This paper presents a reaction-diffusion stereo algorithm with anisotropic diffusion. The reaction-diffusion stereo algorithm detects the stereo disparity, by finding a one-to-one stereo correspondence between the left and right images. There is often ambiguity in finding stereo correspondences because of a lack of texture or similar brightness patterns in objects. In addition, in occluded areas, there is no information by which to find stereo correspondence. Thus, it is necessary to fill in undetected areas of stereo disparity from neighbouring detected areas on a stereo disparity map according to the two constraints of uniqueness and continuity. The reaction-diffusion stereo algorithm realises the continuity constraint with the two different diffusion processes of activation and inhibition. Motivated by psychological evidence from actual human stereo depth perception, this paper proposes the imposition of anisotropic inhibitory diffusion on the algorithm. We apply the proposed anisotropic reaction-diffusion algorithm to several pairs of stereo images and evaluate its performance in comparison to the original reaction-diffusion stereo algorithm. Results of the evaluations show that the addition of anisotropic inhibitory diffusion is partially effective in depth discontinuity areas.
机译:本文提出了一种具有各向异性扩散的反应扩散立体算法。反应扩散立体算法通过找到左右图像之间的一对一立体对应关系来检测立体差异。由于对象中缺乏质感或类似的亮度模式,因此在寻找立体对应关系时通常会含糊不清。另外,在被遮挡的区域中,没有信息可用于找到立体对应关系。因此,有必要根据唯一性和连续性两个约束条件,从立体视差图上的相邻检测区域中填充未检测到的立体视差区域。反应扩散立体算法通过激活和抑制两种不同的扩散过程实现了连续性约束。基于来自实际人类立体声深度感知的心理学证据的启发,本文提出将各向异性抑制扩散强加于该算法。我们将提出的各向异性反应扩散算法应用于几对立体图像,并与原始反应扩散立体算法进行比较来评估其性能。评估结果表明,各向异性抑制扩散的添加在深度不连续区域中是部分有效的。

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