Method for enhancing binary image of array cascade FHN (FitzHugh Nagumo) model stochastic resonance mechanism

Abstract

The invention relates to a method for enhancing a binary image of an array cascade FHN (FitzHugh Nagumo) model stochastic resonance mechanism, comprising the following steps of: firstly, carrying out multidirectional Hilbert scanning on a binary noisy image to reduce the dimension of the binary noisy image into a plurality of paths of one-dimensional signal sequences; respectively inputting a mapped binary sequence to an array parallel FHN neuron model, and regulating the intensity of inner noise to ensure that a parallel system achieves the optimal stochastic resonance state; carrying out weighting operation on a plurality of paths of outputs to obtain a new output sequence, and reconstructing a two-dimensional signal; then, respectively carrying out row scanning and column scanning on the two-dimensional signal, reducing the dimension of the two-dimensional signal again to form a one-dimensional signal sequence, inputting the one-dimensional signal sequence to the array parallel FHN neuron model to obtain two paths of enhanced output signal sequences, and restoring the enhanced output signal sequences into two-dimensional signals; and finally, inputting the two paths of two-dimensional signals to a discriminator and outputting an enhanced binary image. The method can be used for stressing the outline and the detail of an image signal, removing edge burrs and remarkably improving the quality of an image with a low signal to noise ratio.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to a binary image enhancement method based on an array cascaded FHN model stochastic resonance mechanism. Background technique [0002] The image will inevitably be disturbed by noise in the process of acquisition and transmission, resulting in the degradation of image quality. Therefore, the quality of the image enhancement algorithm will directly affect the accuracy and efficiency of subsequent image coding and image analysis. The principle of traditional image enhancement is mainly based on methods such as linear filter, wavelet domain and Markov random field. These methods suppress the noise in the image as a harmful component, which will inevitably weaken the useful information in the image at the same time, so for The effect of image enhancement in the background of strong noise is particularly unsatisfactory. The stochastic resonance mechanism believes that the noise energy ca...

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