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

作者:

Highlights:

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.

论文关键词:3D computer vision,Unified model,Simultaneous parameter estimation,Defocus blur,Disparity,Motion,Zoom,Homotopy method,Generalized moment expansion

论文评审过程:Received 13 June 2002, Accepted 13 January 2003, Available online 29 March 2003.

论文官网地址:https://doi.org/10.1016/S0031-3203(03)00040-2