针对红外图像存在的对比度差、信噪比低等问题，提出了一种基于小波和侧抑制网络的红外图像对比度增强算法。该算法首先利用小波变换法对图像进行小波分解，然后分别采用优化局部阈值和侧抑制网络法对分解后的高频系数和低频系数进行处理，最后进行小波重构，即得到增强后的图像。实验表明：该算法能够在实现图像增强的同时，较好地抑制图像噪声，并可以有效凸显图像的细节。

For infrared image with the characteristics of low contrast and low signal-to-noise, a infrared image enhancement method based on Wavelet Transform and Lateral Inhibition Network is presented. Firstly the wavelet transform is adopted to decompose the input infrared, and then low frequency coefficients are managed by the Lateral Inhibition Network and high frequency coefficients are managed by the optimized Wavelet Part Threshold. Finally, the inverse wavelet transform is applied to synthesis image which can obtain the enhanced image. The experiment show that: at the same time enhances the image, the algorithm can preferable suppress the image noise, and can effectively highlight the image detail.