Publications
Hyperspectral image quality based on convolutional network of multi-scale depth
Abstract
Hyperspectral imagery has been widely used in military and civilian research fields such as crop yield estimation, mineral exploration, and military target detection. However, for the limited imaging equipment and the complex imaging environment of hyperspectral images, the spatial resolution of hyperspectral images is still relatively low, which limits the application of hyperspectral images. So, studying the data characteristics of hyperspectral images deeply and improving the spatial resolution of hyperspectral images is an important prerequisite for accurate interpretation and wide application of hyperspectral images. The purpose of this paper is to deal with super-resolution of the hyperspectral image quickly and accurately, and maintain the spectral characteristics of the hyperspectral image, makes the spectral separability of the substrate in the original image remains unchanged after super-resolution processing …
- Date
- 2020
- Authors
- Lei Liu, Min Sun, Xiang Ren, Xiuxian Li, Qiaoru Zhang, Li Ma, Yongning Li, Mo Song
- Journal
- Journal of Visual Communication and Image Representation
- Volume
- 71
- Pages
- 102721
- Publisher
- Academic Press