基于领域知识驱动的深度学习Pan-sharpening方法

Abstract

Pan-sharpening是将同一场景的全色（PAN）图像和多光谱（MS）图像相互融合以有效提高MS图像的空间分辨率。Pan-sharpening在无需升级硬件的情况下有效克服了单一传感器的物理局限性，因而成为遥感领域的研究热点，并已广泛应用于自然资源探测、环境监测、军事侦察、和灾害监控等领域。 Pan-sharpening的主要目标是在光谱基本不失真的前提下尽可能提高MS图像的空间分辨率，其中MS图像具有较高的谱分辨率但是空间分辨率较低，PAN图像则具有很高的空间分辨率但缺少光谱分辨能力。由于是对同一场景成像，因而MS图像与PAN图像具有相似的图像结构，但是两者成像频段不一致，导致其数值...

Pan-sharpening refers to the process of fusing a panchromatic (PAN) image and a multispectral (MS) image for the same scene to obtain a high resolution multispectral (HRMS) image. Pan-sharpening has overcome the physical limitations of a single sensor effectively without upgrading the hardware,which has led Pan-sharpening to become a hot issue and has been widely used in natural resource explorati...