Infrared image processing method based on lateral inhibition network

Abstract

The invention relates to an infrared image processing method based on a lateral inhibition network. The method comprises the following steps that S1, partial entropy in each pixel point region of an image is calculated so that a partial entropy matrix of the image can be obtained; S2, according to the partial entropy matrix of the whole image, a maximum value of the matrix is calculated and then a measurement operator is constructed; S3, an inhibition coefficient matrix is solved; S4, according to the results obtained through the S2 and the S3, the infrared image is processed and lateral inhibition network output is obtained. According to the different characteristics of an image saltation zone (including edges and details) and a smoothness zone (including backgrounds and noise) in an empty region, the measuring operator is constructed through the image partial entropy. Therefore, the lateral inhibition network has the capacity of edge identification and is strong in noise immunity. After the lateral inhibition network is combined with a filtering mechanism, the image is enhanced and the lateral inhibition network has the noise inhibiting effect.

Description

technical field [0001] The invention relates to the technical field of infrared image enhancement, in particular to an infrared image processing method based on a side suppression network. Background technique [0002] Visual lateral inhibition was first discovered by Hartline and his colleagues in the course of electrophysiological experiments on the compound eye of Limulus. Years of research results have shown that the human visual system also has a lateral inhibition function, which originates from the inhibition between adjacent visual neurons. In the preprocessing stage of visual signals, lateral inhibition is considered to play a crucial role. [0003] The infrared image is imaged by the infrared thermal radiation energy of the target received by the detector. Therefore, compared with the visible light image, the infrared image has the characteristics of low contrast, blurred edges and low signal-to-noise ratio, and the side suppression network is actually a spatial fr...

AI Technical Summary

Problems solved by technology

[0005] Xie Xiaofang, Mao Xiaobo et al. In the article "Research on Improved Image Enhancement Algorithm of Side Suppression Network", they analyzed the difference between the gray value and noise information in the local neighborhood of the image, and proposed a combination of adaptive filtering mechanism and side suppression network. method, which can adaptively adjust the output of the filter according to the mean and variance of the local neighborhood of the image and the variance of the noise. Although this method enhances the image and suppresses the noise to a certain extent, it needs to know the noise variance information in advance, and In actual situations, the noise variance information is often unknown, so it has great limitations

[0006] Through the above analysis, it can be seen that the edge details of the image processed by the existing side suppression network are enhanced, the contrast is improved, but the noise information is also amplified

Some improved algorithms of the side suppression network have a large amount of calculation, which is not conducive to real-time processing, and has large limitations, so it is difficult to be applied in actual situations

Images