针对传统图像增强方法增强图像同时放大噪声的问题,提出了一种基于小波变换和改进模糊集理论进行图像增强的方法。该算法先对原始图像进行小波变换获得低频和高频系数,对低频系数进行了分段函数增强,高频系数进行小波去噪,并且定义新的隶属度函数对各个尺度上不同方向的高频系数进行模糊增强,最后通过小波重构得到增强的图像。实验结果表明,该算法可以有效去除噪声和增强图像,并使图像具有良好的视觉效果。

Focused on the problem that noise is enhanced with image enhancement in the traditional image enhancement methods an image enhancement algorithm based on wavelet transform and improved fuzzy set theory was presented. Firstly, the multi-scale wavelet transform was adopted to decompose the input image. Secondly, the low frequency coefficients were enhanced by the linear piecewise function and wavelet threshold was used for the high frequency coefficients de-noising, then a new membership function of fuzzy was defined and the high frequency coefficients of different directions of each scale were enhanced by fuzzy enhancement transformation. Finally, the inverse wavelet transform was applied to synthesis image. A group of experimental results demonstrate that the disadvantages of traditional enhancement methods are avoided, and the presented algorithm can enhance the key characteristic of the image and restrain noise effectively.