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Proceedings Paper

Preconditioned iterative methods for high-resolution image reconstruction with multisensors
Author(s): Raymond Hon-fu Chan; Tony F. Chan; Michael K. Ng; Wun-Cheung Tang; Chiu-Kwong T. Wong
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Paper Abstract

We study the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. The corresponding reconstruction operators H is a spatially variant operator. In this paper, instead of using the usual zero boundary condition, the Neumann boundary condition 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 preconditioner to solve the discrete problems. Preliminary results how 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.

Paper Details

Date Published: 2 October 1998
PDF: 10 pages
Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); doi: 10.1117/12.325695
Show Author Affiliations
Raymond Hon-fu Chan, Chinese Univ. of Hong Kong (Hong Kong)
Tony F. Chan, Univ. of California/Los Angeles (United States)
Michael K. Ng, Univ. of Hong Kong (Hong Kong)
Wun-Cheung Tang, Chinese Univ. of Hong Kong (Hong Kong)
Chiu-Kwong T. Wong, Univ. of California/Los Angeles (United States)


Published in SPIE Proceedings Vol. 3461:
Advanced Signal Processing Algorithms, Architectures, and Implementations VIII
Franklin T. Luk, Editor(s)

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