融合偏振距离与颜色空间的阴影下目标增强算法

Algorithm of Target Enhancement Under Shadow that Combining Polarization Distance and Color Space

针对阴影造成的低光照、低对比度和高噪声等问题,为提高阴影下目标的检测、识别精度,借鉴生物偏振视觉机理,在偏振距离理论及算法的基础上,提出一种与“色调-饱和度-强度”颜色空间(HSI color space)融合的偏振距离强度(PDI)模型。该模型利用偏振角信息作为估算方式设定阈值范围,将偏振距离信息与原始光强信息融合为新的强度通道,并与原始色调及饱和度信息融合,最终获取PDI模型映射结果。搭建实测实验装置,并开展4组对比实验。结果表明,与其他3种现有目标增强算法相比,所提算法在灰度对比度、信杂比和Fish距离指标上均取得显著提升,能够使阴影下目标与背景间的差异得到明显提高。

Aiming at the problems of low light,low contrast,and high noise caused by shadows,a polarization distance intensity(PDI)model fused with the“hue-saturation-intensity”color space(HSI color space)is proposed based on the theory and algorithm of polarization distance using the biological polarization vision mechanism for reference to improve the detection and recognition accuracy of targets under shadows.The model uses the angle of polarization information as the estimation method to set the threshold range,fuse the polarization distance information and the original light intensity information into a new intensity channel,and fuse with the original hue and saturation information to finally obtain the mapping result of the PDI model.The actual measurement experimental device was set up,and four groups of comparative experiments were conducted.Compared to the other three existing target enhancement algorithms,the proposed algorithm achieves significant improvement in gray contrast,signal-to-clutter ratio,and Fish distance indicators,and could improve the difference between the target and the background under shadow significantly.