基于最小欧氏距离的真彩色夜视光谱划分方法

Spectral partition method of true color night vision based on minimum Euclidean distance

为了得到忠于人眼视觉特性的真彩色夜视图像,根据典型目标夜间光谱特性以及微光夜视系统的成像模型,基于最小欧氏距离原理,提出了一种三波段真彩色夜视光谱划分方法。设置了实验室场景和室外场景,对本文中提出的光谱划分方法与传统光谱划分方法进行了对比实验,并对得到的真彩色夜视图像细节(空间频率)做了分析。结果表明,相对于原始微光图像,空间频率分别提高了61.2%,52.0%;本文中的方法对于典型目标(绿色草木)具有更好的彩色还原效果;基于最小欧氏距离的光谱划分方法可将夜间可见光分离为三波段,并可有效利用其光谱信息,得到对于典型目标的具有自然感彩色且较原始微光图像信息量更为丰富的真彩色夜视图像。

In order to obtain true-color night vision images loyal to the visual characteristics of human eyes,a three-band true-color night vision spectral division method was proposed based on the principle of minimum Euclidean distance according to the night spectral characteristics of typical targets and the imaging model of low-light-level night vision system.The experiments based on spectral division method proposed in this work and the traditional method were set up in laboratory and outdoor scenes.Compared with the traditional spectral division method,the proposed method has a better color restoration effect for typical target(green vegetation).Through the analysis of the details(spatial frequency)of the true-color night vision image obtained by the proposed method,the results show that the spatial frequency increases by 61.2%and 52.0%respectively compared with the original low-light-level images.Therefore,night visible light can be separated into three bands by spectral division method based on minimum Euclidean distance,and its spectral information can be effectively utilized to obtain true color night vision images with natural color and richer information than the original low-light level images for typical targets.