基于神经元阈上非周期随机共振机制的灰度图像复原研究

向学勤; 范影乐; 庞  全; 薛凌云

doi:10.11834/jig.20090114

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基于神经元阈上非周期随机共振机制的灰度图像复原研究
Research on Gray-scale Image Restoration Based on Neuron Suprathreshold Aperiodic Stochastic Resonance Mechanism
2009年14卷第1期页码：77
纸质出版：2009
DOI： 10.11834/jig.20090114
稿件说明：

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向学勤, 范影乐, 庞全, 薛凌云. 基于神经元阈上非周期随机共振机制的灰度图像复原研究[J]. 中国图象图形学报, 2009,14(1):77. DOI： 10.11834/jig.20090114.

XIANG Xueqin, FAN Yingle, PANG Quan, XUE Lingyun1. Research on Gray-scale Image Restoration Based on Neuron Suprathreshold Aperiodic Stochastic Resonance Mechanism[J]. Journal of Image and Graphics, 2009, 14(1): 77. DOI： 10.11834/jig.20090114.

摘要

传统的图像复原方法在重建被噪声污染的图像时，都只是将噪声作为一种干扰加以消除。当噪声增强、图像信号减弱时，由于受方法本身消噪能力的限制，图像的恢复变得非常困难，因此，基于Hodgkin-Huxley神经元阈上非周期随机共振原理，提出了一种通过自适应调节和添加最优噪声的方法来实现图像随机共振，以取得最佳的复原效果。实验结果表明，该方法对于被噪声污染的灰度图像，特别是对于强噪声背景下的灰度图像，其复原的效果优于传统的方法。由于该方法具有较强的鲁棒性，因此为强噪声背景下的图像复原、目标识别等工程应用提供了一种新的思路。

Abstract

As to typical noisy image restoration methods

noise is regarded as a disturbed source.As long as noise becomes strong and image signals become weak

it is difficulty to restore noisy image because of the limitation of these methods.Based on theory of suprathreshold aperiodic stochastic resonance in Hodgkin-Huxley model

a new self-adaptive adjusting adding optimum noise image restoration method is proposed.Results indicate that

as to the restoration effect of gray-scale noisy image

especially strong noisy image

this new method is better than other typical methods used.Thus

this study suggests a new approach in engineering application where under strong noise background

such as image restoration and target identification

given that this new method is of good robustness.