Share Email Print
cover

Proceedings Paper

A novel remote sensing images fusion algorithm combining extended NSST and modified PCNN
Author(s): Huayong Yang; Liyu Lin
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In order to more accurately realize fusion of remote sensing images, we propose a novel remote sensing images fusion algorithm combining extended non-subsampled shearlet transform (NSST) and modified pulse-coupled neural network (PCNN). Firstly, it makes histogram matching and intensity smoothing and filtering treatment on intensity component and full-color image of multi-spectral image. Secondly, such intensity component and full-color image are decomposed by extended NSST to get corresponding high-frequency and low-frequency coefficients. For low-frequency coefficients, fusion is made by sparse representation; for high-frequency coefficients, a modified pulse-coupled neural network (PCNN) strategy is put forward to process. Finally, the processed result is drawn by inverse transformation of the extended NSST and intensity-hue-saturation inverse transformation. The experimental results show that the proposed algorithm reserves as much spectral information as possible and improve spatial resolution; its visual effects and objective indexes are better than other classical fusion algorithms.

Paper Details

Date Published: 9 August 2018
PDF: 10 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080653 (9 August 2018); doi: 10.1117/12.2503367
Show Author Affiliations
Huayong Yang, Wuhan Univ. of Science and Technology (China)
Liyu Lin, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

© SPIE. Terms of Use
Back to Top