Image restoration based on stochastic resonance mechanism of
FitzHugh-Nagumo neuron
XUE Ling-yun1,2, DUAN Hui-long1, XIANG Xue-qin2, FAN Ying-le2
1. Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China;
2. Institute of Biomedical Engineering and Instrument, Hangzhou Dianzi University, Hangzhou 310018, China
Based on stochastic resonance(SR) mechanism, the quality of low signalnoiseratio image was improved by adding noise energy. According to analyzing suprathreshold stochastic resonance and threshold working characteristic of FitzhughNagumo(FHN) neuron model at phase space, the model was simplified. By choosing the peak signaltonoise ratio(PSNR) as estimation function of the image restoration, a selfadaptive optimized algorithm of image restoration processing based on RS mechanism was introduced. A noisy mountain color image, LED chip image and so on, were chosen as experimental objects, to compare simulation result of image restoration with different algorithm, stochastic resonance restoration, mean filter restoration and Wiener filter restoration. The results indicate that SR image restoration method is better in noise inversion, image detail restoration and color information restoration. Along with the increasing of noise intensity, the peak signaltonoise ratio of SR restoration images change less than others. This method has good robustness.
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