Publication
Title
The effect of denoising on superresolution of hyperspectral imaging
Author
Abstract
Hyperspectral Images (HSI) are usually affected by different type of noises such as Gaussian and non-Gaussian. The existing noise can directly affect the classification, unmixing and superresolution analyses. In this paper, the effect of denoising on superresolution of HSI is investigated. First a denoising method based on shearlet transform is applied to the low-resolution HSI in order to reduce the effect of noise, then the superresolution method based on Bayesian sparse representation is used. The proposed method is applied to real HSI dataset. The obtained results of the proposed method in comparison with some of the state-of-the-art superresolution methods show that the proposed method significantly increases the spatial resolution and decreases the noise effects efficiently.
Language
English
Source (journal)
Proceedings of the Society of Photo-optical Instrumentation Engineers / SPIE: International Society for Optical Engineering. - Bellingham, Wash.
Source (book)
Conference on Image and Signal Processing for Remote Sensing XXIII, SEP 11-13, 2017, Warsaw, POLAND
Publication
Bellingham : Spie-int soc optical engineering, 2017
ISSN
0277-786X
ISBN
978-1-5106-1318-8
978-1-5106-1319-5
978-1-5106-1318-8
Volume/pages
10427(2017), 11 p.
Article Reference
1042708
ISI
000425842500006
Medium
E-only publicatie
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 29.03.2018
Last edited 23.08.2021
To cite this reference