NDLI: Super-resolution reconstruction of hyperspectral images

Content Provider	IEEE Xplore Digital Library
Author	Akgun, T. Altunbasak, Y. Mersereau, R.M.
Copyright Year	1992
Abstract	Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.
Sponsorship	IEEE Signal Processing Society
Page Count	16
File Size	3689060
Starting Page	1860
Ending Page	1875
File Format	PDF
ISSN	10577149
Volume Number	14
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Image reconstruction Hyperspectral imaging Hyperspectral sensors Spatial resolution Object detection Target tracking Scattering Lighting Image sensors super resolution Hyperspectral image reconstruction information fusion resolution enhancement spectral
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Superresolution reconstruction of hyperspectral images

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data

Super-resolution reconstruction of hyperspectral images (2005)

Efficient detection in hyperspectral imagery

Integration of Spatial–Spectral Information for Resolution Enhancement in Hyperspectral Images

MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor

Resolution enhancement of hyperspectral images using a learning-based super-resolution mapping technique

Spatially Adaptive Block-Based Super-Resolution

Joint Registration and Super-Resolution With Omnidirectional Images

Super-resolution reconstruction of hyperspectral images

Similar Documents

Superresolution reconstruction of hyperspectral images

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data

Super-resolution reconstruction of hyperspectral images (2005)

Efficient detection in hyperspectral imagery

Integration of Spatial–Spectral Information for Resolution Enhancement in Hyperspectral Images

MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor

Resolution enhancement of hyperspectral images using a learning-based super-resolution mapping technique

Spatially Adaptive Block-Based Super-Resolution

Joint Registration and Super-Resolution With Omnidirectional Images

Super-resolution reconstruction of hyperspectral images