Blind Image De-convolution In Surveillance Systems By Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Kadu:2013:IJARCET,
  author =       "Shweta R. Kadu and A. D. Gawande and L. K Gautam",
  title =        "Blind Image De-convolution In Surveillance Systems By
                 Genetic Programming",
  journal =      "International Journal of Advanced Research in Computer
                 Engineering \& Technology",
  year =         "2013",
  volume =       "2",
  number =       "4",
  pages =        "1415--1419",
  month =        apr,
  keywords =     "genetic algorithms, genetic programming, image blind
                 de-convolution, maximum likelihood, PSF",
  ISSN =         "22781323",
  URL =          "http://ijarcet.org/?p=338",
  bibsource =    "OAI-PMH server at www.doaj.org",
  oai =          "oai:doaj-articles:e04f9e103f8d2c09e8f86bd16ad4ca73",
  URL =          "http://ijarcet.org/wp-content/uploads/IJARCET-VOL-2-ISSUE-4-1415-1419.pdf",
  size =         "5 pages",
  abstract =     "surveillance systems has an important part as image
                 acquisition and filtering, segmentation, object
                 detection and tracking the object in that image. In
                 blind image de-convolution .most of the methods
                 requires that the PSF and the original image must be
                 irreducible. Blurring is a perturbation due to the
                 imaging system while noise is intrinsic to the
                 detection process. Therefore image de-convolution is
                 basically a post-processing of the detected images
                 aimed to reduce the disturbing effects of blurring and
                 noise. Image de-convolution implies the solution of a
                 linear equation ,but this problem turns out to be
                 ill-posed: the solution may not exist or may not be
                 unique. Moreover, even if a unique solution can be
                 found this solution is strongly perturbed by noise
                 propagation.In this papers we proposed a genetic
                 programming based blind-image de-convolution Blind
                 De-convolution algorithm can be used effectively when
                 of distortion is known. It restores image and Point
                 Spread Function (PSF) simultaneously. This algorithm
                 can be achieved based on Maximum Likelihood Estimation
                 (MLE).",
  notes =        "Shri Pannalal Research Institute of Technology.

                 PDF gives date as Jan 2013",
}

Genetic Programming entries for Shweta R Kadu A D Gawande L K Gautam

Citations