针对传统红外图像增强算法中存在的问题, 提出一种结合小波分析与直方图的红外图像增强方法。采用正交小波变换对红外图像进行处理, 得到小波各层的分解系数; 运用双向直方图均衡法对红外图像的低频子带小波系数进行处理, 利用阈值滤波的细节系数增强法对红外图像的高频子带小波系数进行处理, 经小波逆变换图像重构得到增强后的红外图像。实验结果分析表明：该方法可以提高红外图像灰度值, 增加了约一倍的细节信息量, 克服了噪声的放大, 提高了红外图像的对比度、细节和层次感, 是一种有效的红外图像增强方法。

Aiming at several problems of traditional infrared image enhancement algorithm, an infrared image enhancement method based on wavelet analysis and histogram was proposed. Firstly, the wavelet coefficients were obtained by performing orthogonal wavelet transformation. Then the low frequency wavelet coefficients were enhanced by the double histogram equalization method and for the high-frequency wavelet coefficients, the threshold-filtering method was utilized to enhance the details of the image. Finally, the reconstructed infrared image with enhancement was obtained by using the inverse wavelet transform. The experimental results show that the method improves the gray-scale value and dynamics, doubles the detailed information, restrains the noise, and enhances the contrast in infrared images, which is an effective method for infrared image enhancement.