Chinese Optics Letters, 2009, 7 (8): 08686, Published Online: Aug. 17, 2009
Hopfield neural network-based image restoration with adaptive mixed-norm regularization Download: 590次
图像复原 神经网络 混合范数 规整化 100.3020 Image reconstruction-restoration 100.3190 Inverse problems 200.4260 Neural networks
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.
Yuannan Xu, Liping Liu, Yuan Zhao, Chenfei Jin, Xiudong Sun. Hopfield neural network-based image restoration with adaptive mixed-norm regularization[J]. Chinese Optics Letters, 2009, 7(8): 08686.