Record Details

An MRF model-based approach to simultaneous recovery of depth and restoration from defocused images

DSpace at IIT Bombay

View Archive Info
 
 
Field Value
 
Title An MRF model-based approach to simultaneous recovery of depth and restoration from defocused images
 
Creator RAJAGOPALAN, AN
CHAUDHURI, S
 
Subject random-fields
focus
blur
depth from defocus
space-variant blur
space-variant image restoration
markov random field
smoothness constraint
line fields
gibbs distribution
maximum a posteriori
simulated annealing
 
Description Depth from defocus (DFD) problem involves calculating the depth of various points in a scene by modeling the effect that the focal parameters of the camera have on images acquired with a small depth of field. In this paper, we propose a MAP-MRF-based scheme for recovering the depth and the focused image of a scene from two defocused images. The space-variant blur parameter and the focused image of the scene are both modeled as MRFs and their MAP estimates are obtained using simulated annealing. The scheme is amenable to the incorporation of smoothness constraints on the spatial variations of the blur parameter as well as the scene intensity. It also allows for inclusion of line fields to preserve discontinuities. The performance of the proposed scheme is tested on synthetic as well as real data and the estimates of the depth are found to be better than that of the existing window-based DFD technique. The quality of the space-variant restored image of the scene is quite good even under severe space-varying blurring conditions.
 
Publisher IEEE COMPUTER SOC
 
Date 2011-07-31T13:23:32Z
2011-12-26T12:53:02Z
2011-12-27T05:40:07Z
2011-07-31T13:23:32Z
2011-12-26T12:53:02Z
2011-12-27T05:40:07Z
1999
 
Type Article
 
Identifier IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 21(7), 577-589
0162-8828
http://dx.doi.org/10.1109/34.777369
http://dspace.library.iitb.ac.in/xmlui/handle/10054/8133
http://hdl.handle.net/10054/8133
 
Language en