Simultaneous Depth Reconstruction and Restoration of Noisy Stereo Images Using Non-local Pixel Distribution

In this paper, we propose a new algorithm that solves both the stereo matching and the image denoising problem simultaneously for a pair of noisy stereo images. Most stereo algorithms employ L1 or L2 intensity error-based data costs in the MAP-MRF framework by assuming the naive intensity-constancy. These data costs make typical stereo algorithms suffer from the effect of noise severely. In this study, a new robust stereo algorithm to noise is presented that performs the stereo matching and the image denoising simultaneously. In our approach, we redefine the data cost by two terms. The first term is the restored intensity difference, instead of the observed intensity difference. The second term is the non-local pixel distribution dissimilarity around the matched pixels. We adopted the NL-means (Non Local-means) algorithm for restoring the intensity value as a function of disparity. And a pixel distribution dissimilarity is calculated by using PMHD (Perceptually Modified Hausdorff Dista...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Yong Seok Heo (Seoul National University), Kyoung Mu Lee (Seoul National University), and Sang Uk Lee (Seoul National University)
• Keywords: Depth Reconstruction, Noisy Stereo Images, Restoration