基于拉普拉斯金字塔的红外光强与偏振图像融合

Fusion of Infrared Light Intensity and Polarization Image Based on Laplacian Pyramid

利用红外偏振信息(偏振度、偏振角)对目标进行成像,可以更好地抑制图像的背景噪声,提高信噪比。而且偏振信息相对于光强信息一般会蕴含更丰富的目标边缘轮廓信息。因此,提出一种将红外辐射光强图像和偏振度图像进行融合的算法。此方法首先对参与融合的每幅图像分别进行拉普拉斯金字塔分解,获得每层的分解图像;然后对分解后的每层图像采用不同的融合方法进行图像融合,获得每层融合图像,并对每层融合后的图像进行图像重构,得到最后的融合结果。多幅图像融合后的效果表明该方法能够增加图像的信息量,有利于场景感知和目标识别。

Using infrared polarization information(degree of polarization,polarization angle)to image a target can better suppress the background noise of the image and improve the signal-to-noise ratio.In addition,the polarization information generally contains richer edge contour information than the light intensity information.Therefore,an algorithm is proposed to fuse the infrared radiation intensity image and polarization image.This method first performs Laplacian pyramid decomposition on each image participating in the fusion to obtain a decomposed image of each layer;then uses different fusion methods for image fusion for each decomposed image to obtain a fused image of each layer.Image reconstruction is performed on the fused image of each layer to get the final fusion result.The effect of multiple image fusion shows that this method can increase the amount of information in the image,which is beneficial to scene perception and target recognition.