Preconditioned iterative methods for high-resolution image reconstruction with multisensors

Raymond H. Chan*, Tony F. Chan, Michael K. Ng, Wun Cheung Tang, Chiu Kwong Wong

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

22 Scopus citations


We study the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. The corresponding reconstruction operator H is a spatially variant operator. In this paper, instead of using the usual zero boundary condition (corresponding to a dark background outside the scene), the Neumann boundary condition (corresponding to a reflection of the original scene at the boundary) is imposed on the images. The resulting discretization matrix of H is a block-Toeplitz-Toeplitz-block-like matrix. We apply the preconditioned conjugate gradient (PCG) method with cosine transform preconditioners to solve the discrete problems. Preliminary results show that the image model under the Neumann boundary condition gives better reconstructed high-resolution images than that under the zero boundary condition, and the PCG method converges very fast.

Original languageEnglish (US)
Pages (from-to)348-357
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1998
Externally publishedYes
EventAdvance Signal Processing Algorithms, Atchitectures, and Implementations VIII - San diego, CA, United States
Duration: Jul 22 1998Jul 24 1998


  • Block-Toeplitz-Toeplitz-block-like matrix
  • Cosine transform preconditioner
  • High-resolution image reconstruction
  • Neumann boundary condition
  • Preconditioned conjugate gradient
  • Regularization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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