Paper Info
Title
A Super-Resolution and Fusion Approach to Enhancing Hyperspectral Images.
Abstract
High resolution (HR) hyperspectral (HS) images have found widespread applications in terrestrial remote sensing applications, including vegetation monitoring, military surveillance and reconnaissance, fire damage assessment, and many others. They also find applications in planetary missions such as Mars surface characterization. However, resolutions of most HS imagers are limited to tens of meters. Existing resolution enhancement techniques either require additional multispectral (MS) band images or use a panchromatic (pan) band image. The former poses hardware challenges, whereas the latter may have limited performance. In this paper, we present a new resolution enhancement algorithm for HS images that only requires an HR color image and a low resolution (LR) HS image cube. Our approach integrates two newly developed techniques: (1) A hybrid color mapping (HCM) algorithm, and (2) A Plug-and-Play algorithm for single image super-resolution. Comprehensive experiments (objective (five performance metrics), subjective (synthesized fused images in multiple spectral ranges), and pixel clustering) using real HS images and comparative studies with 20 representative algorithms in the literature were conducted to validate and evaluate the proposed method. Results demonstrated that the new algorithm is very promising.
Year
DOI
Venue
2018
10.3390/rs10091416
REMOTE SENSING
Keywords
Field
DocType
hybrid color mapping,Hyperspectral Imaging,Plug-and-Play Alternating Direction Method of Multipliers (PAP-ADMM),remote sensing,super-resolution
Computer vision,Remote sensing,Fusion,Hyperspectral imaging,Artificial intelligence,Geology,Superresolution
Journal
Volume
Issue
ISSN
10
9
2072-4292
Citations 
PageRank 
References 
9
0.46
15
Authors
5
Name
Order
Citations
PageRank
Chiman Kwan144071.64
Choi, Joon Hee2522.51
Stanley H. Chan340330.95
Jin Zhou416322.80
Bence Budavari5536.03