Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selection of Optimal Stopping Time for Nonlinear Diffusion Filtering
International Journal of Computer Vision
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reaction-Diffusion Computers
Reaction-diffusion systems in pattern formation and pattern recognition processes
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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The present paper proposes a novel stereo algorithm utilizing multi-sets of reaction–diffusion equations. The problem of detecting a stereo disparity map becomes the segmentation problem, in which the uniqueness assumption and the continuity assumption on disparity distribution are taken into account. A set of reaction–diffusion equations realizes the continuity assumption, while a mutual-inhibition mechanism among the multi-sets realizes the uniqueness one. In addition, each set of equations has a self-inhibition mechanism, which is necessary for the reaction-diffusion equations applied to stereo disparity detection. Performance of the proposed algorithm is evaluated for well-known test stereo images.