基于相似度测量和模糊熵的矿井图像增强方法

摘要

To improve the image visual effects underground mine, an improved method of combination of enhancement algorithm based on homogeneity measurement and fuzzy entropy theory is proposed. By quoting fuzzy entropy, the criterion based on fuzzy entropy measure is established, to reduce noises as possibly. The algorithm of the membership function is modified for fully extracting the image fractal dimension feature information. The algorithm of the contrast transformation factor is modified for local contrast enhance. The experimental results shows that the algorithm can avoid over-enhancement, and preserve better noise reducing, light and dark contrast and details. The algorithm is an efficiencial image enhancement underground mine.%为了提高煤矿井下图像的视觉效果,提出一种改进的基于相似度测量的增强算法和模糊熵理论相结合的方法.根据煤矿井下图像的特点,引入模糊熵,建立基于模糊熵测度的判别准则,尽量去除噪声干扰.改进隶属度函数的计算方法,充分提取图像中的分形维特征信息.通过改进对比度变换因子的计算方法,进一步增强图像局部对比度.实验结果表明,处理后的图像不会出现增强过度现象,具有较好地噪声抑制、明暗对比和保持图像细节,是一种有效地矿井图像增强方法.