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

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• 作者：Rafael G. Pires ; Danillo R. Pereira ; Luís A. M. Pereira…
• 关键词：Image restoration ; Harmony search ; Projections onto convex sets
• 刊名：Natural Computing
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：15
• 期：3
• 页码：493-502
• 全文大小：1,465 KB
• 刊物类别：Computer Science
• 刊物主题：Theory of Computation
  Evolutionary Biology
  Processor Architectures
  Artificial Intelligence and Robotics
  Complexity
  
• 出版者：Springer Netherlands
• ISSN：1572-9796
• 卷排序：15

文摘

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.