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Simultaneous color consistency and depth map estimation for radiometrically varying stereo images

机译:辐射变化立体图像的同时颜色一致性和深度图估计

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In this paper, we propose a new method that infers accurate depth maps and color-consistent images between radiometrically varying stereo images, simultaneously. In general, stereo matching and performing color consistency between stereo images are a chicken-and-egg problem. Color consistency enhances the performance of stereo matching, while accurate correspondences from stereo disparities improve color consistency between stereo images. We devise a new iterative framework in which these two processes can boost each other. For robust stereo matching, we utilize the mutual information-based method combined with the SIFT descriptor from which we can estimate the joint pdf in log-chromaticity color space. From this joint pdf, we can estimate a linear relationship between the corresponding pixels in stereo images. Using this linear relationship and the estimated depth maps, we devise a stereo color histogram equalization method to make color-consistent stereo images which conversely boost the disparity map estimation. Experimental results show that our method produces both accurate depth maps and color-consistent stereo images even for stereo images with severe radiometric differences.
机译:在本文中,我们提出了一种新方法,该方法可同时推断辐射变化的立体图像之间的准确深度图和颜色一致的图像。通常,立体匹配和在立体图像之间执行颜色一致性是鸡与蛋的问题。颜色一致性增强了立体匹配的性能,而来自立体视差的准确对应关系则改善了立体图像之间的颜色一致性。我们设计了一个新的迭代框架,这两个过程可以相互促进。对于鲁棒的立体声匹配,我们利用基于互信息的方法结合SIFT描述符,从中可以估计对数色度色彩空间中的联合pdf。从这个联合pdf,我们可以估计立体图像中相应像素之间的线性关系。利用这种线性关系和估计的深度图,我们设计了一种立体颜色直方图均衡方法来制作颜色一致的立体图像,从而反过来提高了视差图估计。实验结果表明,即使对于具有严重辐射差异的立体图像,我们的方法也可以生成准确的深度图和颜色一致的立体图像。

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