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Author
Mikhail Mozerov; Joost Van de Weijer
Title
One-view occlusion detection for stereo matching with a fully connected CRF model
Type
Journal Article
Year
2019
Publication
IEEE Transactions on Image Processing
Abbreviated Journal
TIP
Volume
28
Issue
6
Pages
2936-2947
Keywords
Stereo matching; energy minimization; fully connected MRF model; geodesic distance filter
Abstract
In this paper, we extend the standard belief propagation (BP) sequential technique proposed in the tree-reweighted sequential method [15] to the fully connected CRF models with the geodesic distance affinity. The proposed method has been applied to the stereo matching problem. Also a new approach to the BP marginal solution is proposed that we call one-view occlusion detection (OVOD). In contrast to the standard winner takes all (WTA) estimation, the proposed OVOD solution allows to find occluded regions in the disparity map and simultaneously improve the matching result. As a result we can perform only
one energy minimization process and avoid the cost calculation for the second view and the left-right check procedure. We show that the OVOD approach considerably improves results for cost augmentation and energy minimization techniques in comparison with the standard one-view affinity space implementation. We apply our method to the Middlebury data set and reach state-ofthe-art especially for median, average and mean squared error metrics.
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Notes
LAMP; 600.098; 600.109; 602.133; 600.120;ISE
Approved
no
Call Number
Admin @ si @ MoW2019
Serial
3221
Permanent link to this record
Author
Mikhail Mozerov; Joost Van de Weijer
Title
Improved Recursive Geodesic Distance Computation for Edge Preserving Filter
Type
Journal Article
Year
2017
Publication
IEEE Transactions on Image Processing
Abbreviated Journal
TIP
Volume
26
Issue
8
Pages
3696 - 3706
Keywords
Geodesic distance filter; color image filtering; image enhancement
Abstract
All known recursive filters based on the geodesic distance affinity are realized by two 1D recursions applied in two orthogonal directions of the image plane. The 2D extension of the filter is not valid and has theoretically drawbacks, which lead to known artifacts. In this paper, a maximum influence propagation method is proposed to approximate the 2D extension for the
geodesic distance-based recursive filter. The method allows to partially overcome the drawbacks of the 1D recursion approach. We show that our improved recursion better approximates the true geodesic distance filter, and the application of this improved filter for image denoising outperforms the existing recursive implementation of the geodesic distance. As an application,
we consider a geodesic distance-based filter for image denoising.
Experimental evaluation of our denoising method demonstrates comparable and for several test images better results, than stateof-the-art approaches, while our algorithm is considerably fasterwith computational complexity O(8P).
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Notes
LAMP; ISE; 600.120; 600.098; 600.119;CIC
Approved
no
Call Number
Admin @ si @ Moz2017
Serial
2921
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