Affiliation:
1. National Institute of Metrology
Abstract
Fusing a low-spatial-resolution hyperspectral image (LR-HSI) and a high-spatial-resolution RGB image (HR-RGB) is an important technique for HR-HSI obtainment. In this paper, we propose a dual-illuminance fusion-based super-resolution method consisting of spectral matching and correction. In the spectral matching stage, an LR-HSI patch is first searched for each HR-RGB pixel; with the minimum color difference as a constraint, the matching spectrum is constructed by linear mixing the spectrum in the HSI patch. In the spectral correlation stage, we establish a polynomial model to correct the matched spectrum with the aid of the HR-RGBs illuminated by two illuminances, and the target spectrum is obtained. All pixels in the HR-RGB are traversed by the spectral matching and correction process, and the target HR-HSI is eventually reconstructed. The effectiveness of our method is evaluated on three public datasets and our real-world dataset. Experimental results demonstrate the effectiveness of our method compared with eight fusion methods.
Funder
National Natural Science Foundation of China
Beijing Institute of Graphic Communication
Subject
Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Cited by
4 articles.
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