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Projections onto convex sets parameter estimation through harmony search and its application for image restoration

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Author(s):
Pires, Rafael G. ; Pereira, Danillo R. ; Pereira, Luis A. M. ; Mansano, Alex F. ; Papa, Joo P.
Total Authors: 5
Document type: Journal article
Source: NATURAL COMPUTING; v. 15, n. 3, p. 10-pg., 2016-09-01.
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. (AU)

FAPESP's process: 11/14094-1 - Exploring Multi-labeling Approaches by Optimum-Path Forest
Grantee:Luis Augusto Martins Pereira
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 09/16206-1 - New trends on optimum-path forest-based pattern recognition
Grantee:João Paulo Papa
Support Opportunities: Research Grants - Young Investigators Grants
FAPESP's process: 13/20387-7 - Hyperparameter optimization in deep learning arquitectures
Grantee:João Paulo Papa
Support Opportunities: Scholarships abroad - Research
FAPESP's process: 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms
Grantee:João Paulo Papa
Support Opportunities: Regular Research Grants