基于协同表示的高光谱和多光谱图像融合算法

为了增强高光谱图像的空间分辨率，该文提出一种基于传统Pan-sharpening技术的高光谱和多光谱融合框架，该融合框架将高光谱和多光谱(HS-MS)图像融合问题简化为若干个多波段和单波段(MB-IB)图像融合问题。在此基础上，对于每个多波段和单波段图像融合的问题提出一种基于局部自适应(LA)字典和协同表示(CR)的图像融合(LACRF)算法，得到高空间分辨率的多波段(HRMB)图像，并最终获到了高空间分辨率的高光谱图像(HHS)。通过实验可知，LACRF算法具有良好的融合效果。

Hyperspectral and Multispectral Image Fusion Algorithm Based on Collaborative Representation

Based on the traditional Pan-sharpening technology, we propose a high spectral and multispectral integration framework. In the framework, hyperspectral and multispectral image fusion (HS-MS) problem is simplified to a number of multiband and single band (MB-IB) image fusion problems. On this basis, an image fusion algorithm based on collaborative representation using local adaptive dictionary pair (LACRF) algorithm based on local adaptive (LA) dictionary and collaborative representation (CR) is proposed for image fusion of each multi-band and single-band, to obtain multi-band (HRMB) images with high spatial resolution, and finally to obtain hyperspectral images (HHS) with high spatial resolution. According to the experimental results, LACRF algorithm has a better fusion effect.