基于灰度等间距密度均衡的红外图像增强算法

针对红外图像具有高背景,低反差的特点,提出了一种基于灰度级等间距密度均衡的红外图象自适应增强方法。该方法以图像灰度相关理论为基础,采用窗口递推的方式,自适应地选择直方图窗口,获得高低阈值,再通过灰度线性变换及灰度级等间距密度均衡,增大图像灰度动态范围,获得细节丰富灰度连续的图像。理论分析和实验结果均表明,该算法克服了平台直方图均衡引起的灰度断层现象,有效地增强了红外图像的对比度,提高了图像质量。

Infrared Images Enhancement Based-on Balanced Spacing Density of Gray-Scale Equalization

For Infrared images with the background of high and low contrast features,a new adaptive enhancement was put forward based on the balanced spacing density of gray-scale equalization.According to the gray-scale image theory,we used the recursive window,selected the histogram window adaptively and got the high and low thresholds.then,through the gray linear translation and the balanced spacing density of gray-scale,the gray-scale image dynamic range is inereased and the infrared images isobtained with rich detail and continuous gray-scale.Theoretical analysis and experimental results show that,this proposed method overcomes the discontinuous gray caused by the general histogram equalization and plateau histogram equalization,achieves high contrast and greatly improves the quality of infrared images.