一种自适应红外图像增强算法

针对红外图像普遍存在的目标与背景对比度差的特点,提出一种自适应红外图像增强算法.该算法首先采用峰值与局部最大值估算法相结合的方法自适应地计算出两个阈值,由此将图像分为背景段、目标段和过渡段三部分;然后对不同的灰度段采用不同的变换系数分段进行灰度拉伸和压缩变换,实现图像的自适应增强;最后对得到的图像进行灰度间距的均衡化处理,把灰度等级在整个显示范围内等间距排列.实验结果表明,该算法能够实现自适应阈值选择,获得灰度更加连续的红外图像,有效地增加了图像的细节和清晰度.

An adaptive algorithm for infrared image enhancement

Aimed at the character of object-to-background poor contrast of infrared image,an adaptive algorithm for infrared image enhancement was proposed.In this algorithm,two threshold values were evaluated adaptively first by means of combined method of peak value estimation and local maximum value estimation.Then the image was divided into three sections: background,transition and object.Further,the parts with gray scale different were stepwise stretched or compressed with different transform coefficients to acquire adaptive enhancement for the image.Finally,the space between adjacent gray scales of the image was equalized.By so doing,all grades of gray scales in the whole displaying range were arrayed with uniform space to obtain continuous gray scale.The experimental result showed that this algorithm could be used to realize the selection of adaptive threshold values and enhance the details and contrast of the image.