基于模糊熵的自适应图像多层次模糊增强算法

An Adaptive Multi-level Image Fuzzy Enhancement Algorithm Based on Fuzzy Entropy

该文对图像模糊增强算法中的非线性变换进行了较深入的研究,发现了其存在的问题,例如变换的强度较小,运算速度较慢,丢失部分灰度信息等缺点.提出了一种新的模糊增强变换算子,该变换算子不但克服了上述缺点,而且具有封闭性、变换强度可调性以及移植性好等优点.并将该算子成功地引入到多层次图像模糊增强算法中,取得了较好的效果;另外,该文针对以往算法需要人工介入设置阈值参数方可进行图像增强的缺点,通过模糊熵的引入,新算法可以自动地选取最佳的阈值参数而不需人为的介入,因而成功的解决了这一难题;最后,将新的多层次模糊增强算法应用于图像边缘检测中,取得了优于现有模糊增强方法的效果.

The no-linearity transform in image enhancement was researched deeply in the paper,its drawbacks were found.Then,an novel image fuzzy enhancement arithmetic operators was proposed,the arithmetic operators not only overcome the drawbacks of the old no-linearity transform,but also has close-character,adjusting-character and transplantable-character to other enhancement arithmetic.In addition,through quoting fuzzy entropy,make the select of threshold value in image enhancement have a certainty purpose.We use our new algorithm to extract image edges,with better result than that of now-available image fuzzy enhancement method.