Paper Info
Title
SPOT5 multi-spectral (MS) and panchromatic (PAN) image fusion using an improved wavelet method based on local algorithm
Abstract
Remote sensing image fusion is an effective way to extract a large volume of data from multi-source images. However, traditional image fusion methods cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. In this paper, a new wavelet method based on a local algorithm is presented. The proposed method fuses multi-spectral (MS) and panchromatic (PAN) images to improve spatial information and preserve spectral characteristics. The main advantage of the new fusion method is the exploitation of the dependency between neighboring pixels. SPOT5 MS and PAN images were employed to execute the fusion methods. To compare with the new method, the principal component analysis (PCA), wavelet transformation, and PCA-based wavelet (PCA+W) image fusion methods were selected. Qualitative and quantitative analyses and classification accuracy assessment were conducted to evaluate the performance of the fusion methods. The results demonstrate that the new wavelet method based on a local algorithm is better than traditional image fusion methods. The new fusion method can achieve a wide range of balance between high spatial resolution retention and spectral characteristic preservation; thus, the new method is suitable for different applications.
Year
DOI
Venue
2013
10.1016/j.cageo.2013.07.002
Computers & Geosciences
Keywords
Field
DocType
spot5 multi-spectral,image fusion method,spectral characteristic,spatial information,improved wavelet method,image fusion,local algorithm,new method,fusion method,new fusion method,new wavelet method,traditional image fusion method
Spatial analysis,Data mining,Image fusion,Computer science,Artificial intelligence,Local algorithm,Wavelet,Computer vision,Pattern recognition,Panchromatic film,Pixel,Image resolution,Principal component analysis
Journal
Volume
ISSN
Citations 
60,
0098-3004
6
PageRank 
References 
Authors
0.51
11
7
Name
Order
Citations
PageRank
Zhangyu Dong160.51
Zongming Wang27219.71
Dianwei Liu373.32
Bai Zhang4208.49
Ping Zhao560.51
Xuguang Tang682.65
Mingming Jia736641.64