Two-dimensional blind deconvolution using a robust GCD approach

Research output: Contribution to conferencePaperpeer-review


In this paper we examine the applicability of the previously proposed Greatest Common Divisor (GCD) method to blind image deconvolution. In this method, the desired image is approximated as the GCD of the two-dimensional polynomials corresponding to the z-transforms of two or more distorted and noisy versions of the same scene, assuming that the distortion filters are FIR and relatively co-prime. We justify the breakdown of two-dimensional GCD into one-dimensional Sylvester-type GCD algorithms, which lowers the computational complexity while maintaining the noise robustness. A way of determining the support size of the true image is also described. We also provide a solution to deblurring using the GCD method when only one blurred image is available. Experimental results are shown using both synthetically blurred images and real motion-blurred pictures.

Original languageEnglish (US)
Number of pages4
StatePublished - 1997
EventProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA
Duration: Oct 26 1997Oct 29 1997


OtherProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
CitySanta Barbara, CA, USA

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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