论文链接:Remote Sensing | Free Full-Text | Infrared–Visible Image Fusion through Feature-Based Decomposition and Domain Normalization (mdpi.com) 研究目的 设计一种新的红外和可见光图像融合方法,通过消除两种模态图像之间的差异并保留各自的独特信息,从而获得高质量的融合图像。 主要创新点 提出基于特征的...
Infrared and visible image fusion via detail preserving adversarial learning DetailGAN: 通过细节保留对抗性学习实现红外和可见光图像融合 研究背景 现有的方法通常选择源图像的相同显著特征,例如边缘和线条,以集成到融合图像中,使得融合图像包含更多的细节信息。然而,上述方法可能不适用于红外和可见光图像融合。特别地,...
《Infrared and Visible Image Fusion using a Deep Learning Framework》论文笔记 主要思路:使用低通滤波器将图片分解lowpass层和highpass层。lowpass层使用加权平均进行融合;highpass使用vgg19做网络的特征提取,取2、7、12、21层。对每层特征先进行了l1-norm将通道数缩放到1,对特征图中的每一个点的邻点做平均A1...
使用本文的DIVFusion应用到高级视觉任务上(行人检测),通过定性、定量的分析,发现本文的方法产生比较好的促进作用。将红外图像、可见光图像、(SOTA+包括我们的方法)融合图像分别送到YOLO5图像检测方法中去进行行人检测任务,可以发现我们的方法达到了最好的效果,因此说明我们提出的融合模型有利于进行高级计算机视觉任务 结...
An infrared and visible fusion imaging system is built to verify the effectiveness and performance of the proposed method. Experimental results on a public dataset and the practical dataset obtained from the experimental system show that the proposed method performs favorably against the nine state-of...
Infrared and visible image fusion is a key area of research in multi-sensor image fusion. The main purpose of this fusion is to combine thermal information of the infrared image and texture information of the visible image. This paper presents an image fusion framework, based on parallel arrange...
In this paper, we propose an effective image fusion method using a deep learning framework to generate a single image which contains all the features from infrared and visible images. First, the source images are decomposed into base parts and detail content. Then the base parts are fused by ...
The most fundamental purpose of infrared (IR) and visible (VI) image fusion is to integrate the useful information and produce a new image which has higher reliability and understandability for human or computer vision. In order to better preserve the interesting region and its corresponding detail...
We have extended our previous capabilities for fusion of multiple passive imaging sensors to now include 3D imagery obtained from a prototype flash ladar. Real-time fusion of SWIR + uncooled LWIR and low-light visible + LWIR + 3D LADAR is demonstrated. Fused visualization is achieved by opponent...
VGG-19 and the multilayer fusion strategy-based method (VggML) DeepFuse DenseFuse FusionGAN IFCNN 图10 实验图像“men”(a)红外图像;(b)可见图像;(c)CBF;(d)DCHWT;(e)JSR;(f)JSRSD;(g)GTF;(h)WLS;(i)ConvSR;(j)VggML; (k)DeepFuse;(l)DenseFuse;(m)IFCNN;(n)FusionGAN;(o)NestFuse(平均...