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High-Resolution Color Image Reconstruction with Neumann Boundary Conditions

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  • Michael Ng
  • Wilson Kwan

Abstract

This paper studies the application of preconditioned conjugate gradient methods in high-resolution color image reconstruction problems. The high-resolution color images are reconstructed from multiple undersampled, shifted, degraded color frames with subpixel displacements. The resulting degradation matrices are spatially variant. To capture the changes of reflectivity across color channels, the weighted H 1 regularization functional is used in the Tikhonov regularization. The Neumann boundary condition is also employed to reduce the boundary artifacts. The preconditioners are derived by taking the cosine transform approximation of the degradation matrices. Numerical examples are given to illustrate the fast convergence of the preconditioned conjugate gradient method. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • Michael Ng & Wilson Kwan, 2001. "High-Resolution Color Image Reconstruction with Neumann Boundary Conditions," Annals of Operations Research, Springer, vol. 103(1), pages 99-113, March.
    • Handle: RePEc:spr:annopr:v:103:y:2001:i:1:p:99-113:10.1023/a:1012990619503
    DOI: 10.1023/A:1012990619503
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    Cited by:

    1. Ha Che-Ngoc & Thao Nguyen-Trang & Tran Nguyen-Bao & Trung Nguyen-Thoi & Tai Vo-Van, 2022. "A new approach for face detection using the maximum function of probability density functions," Annals of Operations Research, Springer, vol. 312(1), pages 99-119, May.

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