Comparison and study of image deconvolution algorithms

Yang Yang Liu*, Wei Qi Jin, Bing Hua Su

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Deconvolution results may deviate true answers because of noise and low pass filtering. The effects of noise and blurred function to image data are compared and studied for several common deconvolution algorithms, and the maximum likelihood algorithm based on the Poisson-Markov model of super-resolution image restoration algorithms is proposed. Experiments showed that, based on the MPML algorithm proposed, it has the advantages of diminishing losses of original data in contrast to other algorithms, especially in cases involving lower noise. The recovery images display very small concussive lines and have better super-resolution recovery ability for deconvolution applications.

Original languageEnglish
Pages (from-to)905-909
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume24
Issue number10
Publication statusPublished - Oct 2004

Keywords

  • Deconvolution
  • Image reconstruction
  • MPML algorithm

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