摘要
针对红外图像整体亮度偏暗、对比度较低、目标与背景区分不明显的特点,论文提出了一种基于模糊最大熵和改进的S函数的图像增强算法。该方法首先通过模糊最大熵准则求取最佳阈值,再使用改进的S函数对阈值两侧的像素灰度进行模糊域的非线性拉伸,从而得到增强后的红外图像。实验结果表明,该算法能明显提高红外图像对比度,突出目标并降低背景噪声。
Considering the characteristics of low luminance,low contrast and the inconspicuous difference between targets and backgrounds in infrared images,an enhancement method based on maximal fuzzy entropy and improved adjustment function is designed.To enhance the target area in infrared images,firstly,an optimal threshold is searched through the maximal Fuzzy- Entropy criterion,and a non-linear stretching method in fuzzy sets is carried out respectively to the pixels on both sides of the threshold.Results of the experiment indicate that the method could well improve the contrast of infrared images,the targets of which are outstanding from the backgrounds,thus strengthening the details of targets and suppressing background noises in the infrared images.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第9期200-201,222,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60402004)
关键词
红外图像
模糊最大熵
图像增强
模糊逻辑
infrared images
maximal fuzzy entropy
image enhancement
fuzzy logic
