Improved estimation of defocus blur and spatial shifts in spatial domain:: a homotopy-based approach

被引:7
|
作者
Deschênes, F
Ziou, D
Fuchs, P
机构
[1] Univ Sherbrooke, Dept Math & Informat, Quebec City, PQ J1K 2R1, Canada
[2] Ecole Mines Paris, Ctr Robot, F-75272 Paris 06, France
关键词
3D computer vision; unified model; simultaneous parameter estimation; defocus blur; disparity; motion; zoom; homotopy method; generalized moment expansion;
D O I
10.1016/S0031-3203(03)00040-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a homotopy-based algorithm for the recovery of depth cues in the spatial domain. The algorithm specifically deals with defocus blur and spatial shifts, that is 2D motion, stereo disparities and/or zooming disparities. These cues are estimated from two images of the same scene acquired by a camera evolving in time and/or space. We show that they can be simultaneously computed by resolving a system of equations using a homotopy method. The proposed algorithm is tested using synthetic and real images. The results confirm that the use of a homotopy method leads to a dense and accurate estimation of depth cues. This approach has been integrated into an application for relief estimation from remotely sensed images. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:2105 / 2125
页数:21
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