Super-Resolution Restoration for Image Based on Entropy Constraint and Projection onto Convex Set

Xiao Qin Li; Kang Ling Fang; Can Jin

doi:10.4028/www.scientific.net/AMR.468-471.1041

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Super-Resolution Restoration for Image Based on...

Super-Resolution Restoration for Image Based on Entropy Constraint and Projection onto Convex Set

Abstract:

Super-resolution reconstruction for image breaks through the resolution limit of imaging systems without hardware change. The algorithm of projection onto convex set (POCS) is a typical super-resolution reconstruction algorithm in spatial domain. The classical algorithm of POCS lacks the overall constraint for the image, and the convergence rate for iteration is incontrollable. A new super-resolution restoration algorithm for image based on entropy constraint and POCS is proposed in this paper, and experiments with optical and millimeter wave images demonstrate that the new algorithm is effective in improving the precision of super-resolution restoration.

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Periodical:

Advanced Materials Research (Volumes 468-471)

Pages:

1041-1048

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.1041

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Online since:

February 2012

Authors:

Xiao Qin Li, Kang Ling Fang, Can Jin

Keywords:

Entropy Constraint, POCS, Reconstruction, Super-Resolution

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References

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