A hierarchical genetic algorithm for disparity estimation is presented. The goal, to estimate reliable disparity fields with low computational cost, is reached using a hierarchical genetic matching procedure. Firstly, each hierarchical image of the stereo pair is divided into sets of feature points and non-feature points. The image morphological gradient for feature points and the disparity Laplacian function for non-feature points are incorporated into the matching function to serve as an adaptive smoothness term. Meanwhile, the vertical-discontinuity constraint and the ordering constraint are also proposed to smooth out vertical disparity discontinuities and to obtain a more reliable disparity estimation. In the hierarchical genetic matching procedure, previously estimated vectors at the former image hierarchy are used to predict the corresponding searching space of chromosomes, and to correct each newly calculated set of disparity vectors. This significantly increases the accuracy of disparity estimation
|Translated title of the contribution||A Hierarchical Genetic disparity Estimation Algorithm for Multiview Image Synthesis|
|Title of host publication||IEEE Int. Conf. on Image Processing (ICIP), Vancouver|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||768 - 771|
|Publication status||Published - Sep 2000|
|Event||International Conference on Image Processing (2000) - Vancouver, BC, Canada|
Duration: 1 Sep 2000 → …
|Conference||International Conference on Image Processing (2000)|
|Period||1/09/00 → …|
Bibliographical noteRose publication type: Conference contribution
Sponsorship: The authors acknowledge to the support of the Virtual Centre of Excellence in Digital Broadcasting and Multimedia Technology (Theme 1) for the financial support of the work
This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org.
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.