Paper Info
Title
Using Synthetic Variable ratio Method to Fuse Multi-source Remotely Sensed Images Based on Sensor Spectral Response
Abstract
Synthetic variable ratio (SVR) method was first introduced to fuse panchromatic (PAN) image and multi-spectral (MS) image by Muechika et al. in 1993(1), and was improved by Zhang Y. in 1999 and 2001 respectively (2, 3). As for Muechika SVR method, it isn't suitable for fusing PAN and MS which cover large area. And for Zhang Y. SVR(ZY-SVR) method, on the one hand it needs to select a great number of pixels of different land coverage classes to conduct multiple regression analysis and thus it seems greatly empirical; on the other hand the coefficients obtained through regression lacks physical meanings. This paper puts forward a new method called LAB-SRV which introduces the sensor spectral response into SVR method using the CIELab color space. The steps of the method are as follow: (1) register the input MS to PAN and the resample it to the same spatial resolution as that of PAN;(2) transform the input MS image from RGB to CIELAB color space to obtain the lightness component (L) and two chromatic components: the a component and the b component; (3) calculate the coefficients for each band of MS for synthesizing the high resolution synthetic panchromatic image HSyn
Year
DOI
Venue
2008
10.1109/IGARSS.2008.4779187
IGARSS
Keywords
Field
DocType
spatial resolution,multiple regression analysis,data mining,image fusion,image sensors,remote sensing,variable ratio,high resolution,color space,remote monitoring,probability density function,image resolution,indexes,fuses,sensor fusion
Computer vision,Color space,Image fusion,Computer science,Panchromatic film,Remote sensing,Artificial intelligence,Pixel,Fuse (electrical),Probability density function,Multi-source,Image resolution
Conference
Citations 
PageRank 
References 
0
0.34
1
Authors
5
Name
Order
Citations
PageRank
Sheng Chen100.34
Jian-Cheng Luo29920.75
Zhanfeng Shen36812.60
Geping Luo4123.49
Changming Zhu55814.51