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Chinese Optics Letters

Chinese Optics Letters

| PUBLISHED MONTHLY BY CHINESE LASER PRESS AND DISTRIBUTED BY OSA

  • Vol. 7, Iss. 8 — Aug. 1, 2009
  • pp: 686–689

Hopfield neural network-based image restoration with adaptive mixed-norm regularization

Yuannan Xu, Liping Liu, Yuan Zhao, Chenfei Jin, and Xiudong Sun  »View Author Affiliations


Chinese Optics Letters, Vol. 7, Issue 8, pp. 686-689 (2009)


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Abstract

To overcome the shortcomings of traditional image restoration model and total variation image restoration model, we propose a novel Hopfield neural network-based image restoration algorithm with adaptive mixed-norm regularization. The new error function of image restoration combines the L2-norm and L1-norm regularization types. A method of calculating the adaptive scale control parameter is introduced. Experimental results demonstrate that the proposed algorithm is better than other algorithms with single norm regularization in the improvement of signal-to-noise ratio (ISNR) and vision effect.

© 2009 Chinese Optics Letters

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(200.4260) Optics in computing : Neural networks

Citation
Yuannan Xu, Liping Liu, Yuan Zhao, Chenfei Jin, and Xiudong Sun, "Hopfield neural network-based image restoration with adaptive mixed-norm regularization," Chin. Opt. Lett. 7, 686-689 (2009)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-7-8-686


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