针对荧光图象的自适应模糊增强算法

Adaptive Image Enhancement Algorithm Based on Fuzzy Sets for Fluorescent Light Image

针对在紫外线激发下的荧光图象，详细分析了其噪声模型，并利用信号检测理论得出了最佳门限的选取方法，同时提出了一种自适应的模糊对比度增强算子，从而使强噪声荧光图象的噪声削弱，图象增强．通过实验证明，基于模糊集的图象自适应增强算法的物理概念清晰，实现容易，对于荧光图象有较好的处理效果．最后通过对模糊度的比较，在理论上验证了算法的有效性．

In this article we analyse in detail the noise model for the fluorescent light image which is stimulated by the ultraviolet ray,and give an optimum threshold based on signal detect theory. Also, we use an adaptive Contrast intensification Operator using Fuzzy Sets. Through a modified process,the fluorescent light image with strong noises will be enhanced by stressing the useful information. Experiments show that the algorithm is easy to get the better effect of enhancement in fluorescent-light image.