基于HSV空间的红外偏振图像改进融合算法

研究了偏振产生的原理和基于标准HSV颜色空间的偏振融合,并根据红外偏振图像对比度较强、强度较弱的特点改进了HSV融合算法,利用原始偏振图像的灰度均值和极值进行图像强度修正,计算融合权重,进行偏振图像融合,增强红外偏振融合图像的强度和对比度。对室内以及室外人造目标进行实验验证,改进的HSV融合算法较红外原图灰度均值最高提升216%,对比度最高提升1384%;较标准HSV融合图像的灰度均值最高提升1363%,对比度最高提升292%。为使用红外偏振融合图像进行目标识别打下了很好的基础。

Improved infrared polarization imaging fusion based on HSV

The theory of polarization and the image fusion based on standard HSV are studied. According to the characteristic of strong contrast and weak intensity in infrared polarization image,the improved HSV fusion algorithm is proposed. By using average gray scale and extreme value of original polarization image,the image intensity was corrected;the fusion weight was calculated; the polarization image was fused;the contrast and intensity of infrared polarization image was enhanced. The experiments indoor and outdoor has been done,the results show the HSV fusion method can enhance the average gray scale by 216% at most,and the contrast improved 1384% at most compared to origin IR images;It also has an improvement of 1363% average gray scale and 292% contrast compared to standard HSV. The algorithm is helpful to enhance the average gray-scale and contrast of the polarization images.