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.
Highlights
The Hyperspectral Infrared Imager (HyspIRI) [1,2,3] is a future NASA mission to provide global coverage with potential applications in detecting changes, mapping vegetation, identifying anomalies, and assessing damages due to flooding, hurricanes, and earthquakes
This paper presents a new resolution enhancement method for hyperspectral images that improve the resolution by injecting information from High resolution (HR) color images acquired by other types of imagers, such as satellite or airborne image sensors, to the low resolution (LR) HS image
A new fusion based algorithm to enhance the resolution of hyperspectral images is presented
Summary
The Hyperspectral Infrared Imager (HyspIRI) [1,2,3] is a future NASA mission to provide global coverage with potential applications in detecting changes, mapping vegetation, identifying anomalies, and assessing damages due to flooding, hurricanes, and earthquakes. The HyspIRI imager offers a 60-m resolution, which is typically enough for these applications. For particular applications such as crop monitoring or mineral mapping, the 60-m resolution remains too coarse. In a recent paper [4], the authors made a comprehensive comparison between more than 10 fusion methods for hyperspectral images. It will be a good contribution to the research community if one can investigate on how to incorporate PSF into those fusion methods that have not yet incorporated PSF and see the impact of those changes on those methods
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