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Scale trees for stereo vision

Moravec, KL; Harvey, R; Bangham, JA; (2000) Scale trees for stereo vision. IEE Proceedings - Vision, Image and Signal Processing , 147 (4) 363 - 370.

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Abstract

The image trees described hierarchically organise image segments according to scale, with the coarsest scale, the scale of the image itself as the root of the tree and the finest scales as the leaves. The segmentation algorithm used to form the tree nodes is the sieve, a nonlinear morphological scale-space operator. The trees are a transform, so it is possible to reconstruct the associated image without loss. Scale trees may have more nodes than are needed but the trees may be simplified using a standard statistical test to reduce the number of nodes without affecting the reconstructed image significantly. These simplified trees may be used to generate regions for a stereo algorithm that reduces the errors in the resulting disparity map, particularly within sharp edged regions with low texture - conditions where conventional methods often fail.

Type:Article
Title:Scale trees for stereo vision
Publisher version:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=872721
Language:English
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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