摘要
由于红外车辆目标在成像过程中存在许多不确定性即模糊性,针对红外图像的模糊性将模糊理论应用于红外图像增强处理,本文提出了一种新的基于模糊理论的图像质量测量函数,把它作为遗传算法的适应度函数对非完全Beta函数的α和β参数进行自适应动态调节来拟合几种典型的灰度变换曲线,实现了感兴趣区域红外车辆目标的自适应模糊增强。实验结果表明了该方法的合理性和有效性,在性能上优于传统的图像增强技术和现有的一些同类增强技术,具有较高的自适应性和智能性。
Because of uncertainties,that is the fuzziness in the infrared vehicle target image processing, fuzzy theory is used in the infrared image processing. A new kind of image measure function is presented by fuzzy theory. As the fitness function of genetic algorithm to it is used adaptively optimize parameter α and β in in-complete Beta function. Thus an optimal gray transformation curve is obtained to enhance the region of interest for an infrared vehicle target image. Experimental results show that this method has higher adaptiviness and intelligence. Compared with the classical image enhancement methods and some existing similar methods,this method is better in performance .
出处
《科学技术与工程》
2009年第10期2592-2596,共5页
Science Technology and Engineering
关键词
红外车辆目标
图像增强
模糊几何特征
遗传算法
infrared vehicle target image enhancement fuzzy geometric feature genetic algorithm
