Hyperspectral VNIR-SWIR image fusion on cultural heritage and remote sensing datasets using image sharpening techniques

Jose N. G. M. Macalintal; Amir Hassanzadeh; David Messinger

doi:10.1117/12.3012711

7 June 2024 Hyperspectral VNIR-SWIR image fusion on cultural heritage and remote sensing datasets using image sharpening techniques

Jose N. G. M. Macalintal, Amir Hassanzadeh, David Messinger

Author Affiliations +

Proceedings Volume 13031, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXX; 130310O (2024) https://doi.org/10.1117/12.3012711
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

Hyperspectral imaging is one of the prevailing tools for the analysis of material composition and feature identification in images. The spectral features contained within image pixels are studied to better understand a pixel’s material composition. However, a major limitation of using a single hyperspectral image sensor is that not all distinguishing spectral features of an image are captured within the conventional operating wavelength bands of a single hyperspectral sensor. While a straightforward solution of using a single hyperspectral sensor with larger wavelength ranges can address such an issue, this is often met with external limiting factors such as sensor availability or costs of operations. Therefore, in order to overcome the limitations of a single-sensor approach, there is motivation to integrate information from multiple sensors instead to create a more useful and accurate representation of a real-world scene. A particular challenge is that different sensors typically produce images of the same scene but at different spatial and spectral resolutions. In this study, we attempt to fuse VNIR and SWIR hyperspectral images and evaluate the fused images’ performance as applied to Cultural Heritage. Specifically, image fusion is performed on a medieval manuscript referred to as the Italian Leaf provided by the University of Durham.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jose N. G. M. Macalintal, Amir Hassanzadeh, and David Messinger "Hyperspectral VNIR-SWIR image fusion on cultural heritage and remote sensing datasets using image sharpening techniques", Proc. SPIE 13031, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXX, 130310O (7 June 2024); https://doi.org/10.1117/12.3012711

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available