Artículos de revistas
Projections onto convex sets parameter estimation through harmony search and its application for image restoration
Fecha
2016-09-01Registro en:
Natural Computing, v. 15, n. 3, p. 493-502, 2016.
1572-9796
1567-7818
10.1007/s11047-015-9507-4
2-s2.0-84936803369
2-s2.0-84936803369.pdf
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
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.