Blind image deconvolution through support vector regression

IEEE Trans Neural Netw. 2007 May;18(3):931-5. doi: 10.1109/TNN.2007.891622.

Abstract

This letter introduces a new algorithm for the restoration of a noisy blurred image based on the support vector regression (SVR). Experiments show that the performance of the SVR is very robust in blind image deconvolution where the types of blurs, point spread function (PSF) support, and noise level are all unknown.

Publication types

  • Evaluation Study
  • Letter

MeSH terms

  • Algorithms*
  • Artificial Intelligence*
  • Computer Simulation
  • Image Interpretation, Computer-Assisted / methods*
  • Information Storage and Retrieval / methods*
  • Models, Theoretical*
  • Neural Networks, Computer
  • Pattern Recognition, Automated / methods*
  • Regression Analysis