Blind deconvolution of blurred images with fuzzy size detection of point spread function

Salman Hameed Khan*, Muhammad Sohail, Ahmed Rehan, Zeashan Hameed Khan, Arsalan Hameed Khan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The objective of present research is to find the correct dimensions of point spread function (PSF), which is a crucial step in blind deconvolution of linearly blurred images. Usually size of PSF is estimated by trial and error, based on user experience. Keeping in view the fuzzy nature of this problem, we have implemented a fuzzy inference system (FIS) in Matlab to efficiently predict the size of PSF. The fuzzy system is based on the common observation that the size of PSF is directly related to the amount of degradation caused to each pixel in the original image. The blurred image is compared with edge extracted image and the PSF size is estimated by accounting for the distortion of edges. The results are encouraging and the method presented in this paper can be used to avoid trial and error based lengthy process of PSF size estimation.

Original languageEnglish
Title of host publicationEmerging Trends and Applications in Information Communication Technologies - Second International Multi Topic Conference, IMTIC 2012, Proceedings
Pages261-271
Number of pages11
DOIs
StatePublished - 2012
Externally publishedYes

Publication series

NameCommunications in Computer and Information Science
Volume281 CCIS
ISSN (Print)1865-0929

Keywords

  • blurred image
  • deconvolution
  • fuzzy logic
  • point spread function

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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