DocumentCode :
1796269
Title :
Affinity Pansharpening and Image Fusion
Author :
Tierney, Stephen ; Junbin Gao ; Yi Guo
Author_Institution :
Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia
fYear :
2014
fDate :
25-27 Nov. 2014
Firstpage :
1
Lastpage :
8
Abstract :
A novel framework for enhancing the resolution of a low-resolution multispectral or hyperspectral image using a high resolution panchromatic image or multispectral image is proposed in this paper. This framework can be further used to perform more general types of image fusion. To create the enhanced image, a convex objective function is minimised, which preserves both the pixel affinity learnt from the high resolution image and spectral information from the low resolution image. A fast approximation method is discussed. Quantitive and qualitative analysis against existing methods shows that our method is comparable to state of the art with faster running time and greater flexibility. MATLAB code for our proposed method and the compared methods are freely available in the FuseBox package.
Keywords :
hyperspectral imaging; image enhancement; image resolution; mathematics computing; sensor fusion; FuseBox package; MATLAB code; affinity pansharpening; convex objective function; fast approximation method; high resolution image; high resolution panchromatic image; hyperspectral image; image enhancement; image fusion; low resolution image; low-resolution multispectral image; pixel affinity; spectral information; Approximation methods; Image fusion; Principal component analysis; Remote sensing; Satellites; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital lmage Computing: Techniques and Applications (DlCTA), 2014 International Conference on
Conference_Location :
Wollongong, NSW
Type :
conf
DOI :
10.1109/DICTA.2014.7008094
Filename :
7008094
Link To Document :
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