IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Correspondence by Dynamic Programming on a Tree
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Disparity Map Estimation Using A Total Variation Bound
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
A convex optimization approach for depth estimation under illumination variation
IEEE Transactions on Image Processing
Vector lifting schemes for stereo image coding
IEEE Transactions on Image Processing
A block-iterative surrogate constraint splitting method for quadratic signal recovery
IEEE Transactions on Signal Processing
Transform coding of stereo image residuals
IEEE Transactions on Image Processing
Image restoration subject to a total variation constraint
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Overlapped block disparity compensation with adaptive windows for stereo image coding
IEEE Transactions on Circuits and Systems for Video Technology
A family of wavelet-based stereo image coders
IEEE Transactions on Circuits and Systems for Video Technology
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Research in stereo image coding has focused on the disparity estimation/ compensation process to exploit the cross-view redundancies. Most of the reported methods use a classical block-based technique in order to estimate the disparity field. However, this estimation technique does not always provide an accurate disparity map, which may affect the disparity compensation step. In this paper, we propose to use an estimation method that produces a dense and smooth disparity map. Then, on the one hand, this map is segmented and efficiently coded by exploiting the high correlation between neighboring disparity values. On the other hand, we integrate the disparity information into a vector lifting scheme for stereo image coding. Experimental results indicate that the proposed coding scheme outperforms the conventional methods employing a block-based disparity estimation.