Genetic programming based blind image deconvolution for surveillancesystems

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Muhammad Tariq Mahmood and Abdul Majid and 
                 Jongwoo Han and Young Kyu Choi",
  title =        "Genetic programming based blind image deconvolution
                 for surveillancesystems",
  journal =      "Engineering Applications of Artificial Intelligence",
  volume =       "26",
  number =       "3",
  pages =        "1115--1123",
  year =         "2013",
  keywords =     "genetic algorithms, genetic programming, Surveillance
                 systems, Deconvolution, Image restoration, Deblurring",
  ISSN =         "0952-1976",
  DOI =          "doi:10.1016/j.engappai.2012.08.001",
  URL =          "",
  abstract =     "Image acquisition, segmentation, object detection and
                 tracking are essential parts of surveillance systems.
                 Usually, image filtering approaches are employed as
                 preprocessing step to reduce the effect of motion or
                 out-of-focus blur problem. In this paper, we propose
                 genetic programming (GP) based blind-image
                 deconvolution filter. A GP based numerical expression
                 is developed for image restoration which optimally
                 combines and exploits dependencies among features of
                 the blurred image. In order to develop such function,
                 first, a set of feature vectors is formed by
                 considering a small neighbourhood around each pixel. At
                 second stage, the estimator is trained and developed
                 through GP process that automatically selects and
                 combines the useful feature information under a fitness
                 criterion. The developed function is then applied to
                 estimate the image pixel intensity of the degraded
                 images. The performance of filter function is estimated
                 using various degraded image sequences. Our comparative
                 analysis highlight the effectiveness of GP based
                 proposed filter.",

Genetic Programming entries for Muhammad Tariq Mahmood Abdul Majid Jongwoo Han Young Kyu Choi