Title
Projections onto convex sets parameter estimation through harmony search and its application for image restoration
Abstract
Image restoration is a research field that attempts to recover a blurred and noisy image. Although we have one-step algorithms that are often fast for image restoration, iterative formulations allow a better control of the trade-off between the enhancement of high frequencies (image details) and noise amplification. Projections onto convex sets (POCS) is an iterative--and parametric-based approach that employs a priori knowledge about the blurred image to guide the restoration process, with promising results in different application domains. However, a proper choice of its parameters is a high computational burden task, since they are continuous-valued and there are an infinity of possible values to be checked. In this paper, we propose to optimize POCS parameters by means of harmony search-based techniques, since they provide elegant and simple formulations for optimization problems. The proposed approach has been validated in synthetic and real images, being able to select suitable parameters in a reasonable amount of time.
Year
DOI
Venue
2016
10.1007/s11047-015-9507-4
Natural Computing: an international journal
Keywords
Field
DocType
Image restoration,Harmony search,Projections onto convex sets
Projections onto convex sets,A priori and a posteriori,Parametric statistics,Harmony search,Artificial intelligence,Image restoration,Estimation theory,Real image,Optimization problem,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
15
3
1567-7818
Citations 
PageRank 
References 
1
0.38
11
Authors
5