International Journal of Education and Management Engineering(IJEME)

ISSN: 2305-3623 (Print), ISSN: 2305-8463 (Online)

Published By: MECS Press

IJEME Vol.2, No.5, May. 2012

Study on Data Fusion Algorithms of Landsat7 ETM+ PAN and Multi-spectral Imagery

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Zhihui Wang,Ximin Cui,Debao Yuan,Guo Wang,Kai Kang

Index Terms

Data fusion algorithm; PAN and multi-spectral; algorithm evaluation; ETM+


Fusion of images with different spatial resolution can improve visualization of the images involved. This study tries to show that the fusion of the images from the same sensor system can improve quality of the original images. Four image fusion algorithms were used in the study of data fusion of Landsat 7 ETM+ imagery, taking southeastern part of Beijing City as the case study, they are the Smoothing Filter-Based Intensity Modulation (SFIM), High-Pass Filter (HPF) Transform, Brovey Transform, Multiplication (MLT) Transform. The effectiveness of the four fusion algorithms has been evaluated based on mean, deviation, information entropy, average gradient and correlation. The study reveals that the SFIM transform is the best method in retaining spectral information of original image, which does not cause spectral distortion and it has highest spatial frequency information. Therefore, fused images from the same sensor system can be used for improving visual interpretation and data quality.

Cite This Paper

Zhihui Wang,Ximin Cui,Debao Yuan,Guo Wang,Kai Kang,"Study on Data Fusion Algorithms of Landsat7 ETM+ PAN and Multi-spectral Imagery", IJEME, vol.2, no.5, pp.1-6, 2012.


[1] Liu J G. Evaluation of Landsat7 ETM+ Panchromaic Band for Image fusion with Multispectral Bands[J]. Natural Resources Research,2000,9(4):269-276.

[2] Chavez P S Jr,Sliders S C,Anderson J A.Comparion of Three Different Methods to Merge Multiresolution Data:Landsat TM and SPOT Panchromatic[J]. Photogrammetric Engineering and Remote Sensing,1991,57(3):295-303

[3] Pohl C,Genderen J L van. Multisensor Image Fusion in Remote Sensing:Concepts,Methods and Applications[J]. International Journal of Remote Sensing,1998,19(5):823-854

[4] Zhao Y S,Li J W. A Study on Land Use Classification Using ETM+[J]. Remote Sensing Information (in Chinese),2001,(2):39-42.

[5] Chen D C,Zhou H B,Chen Z Y et al. Study on Fusion Algorithms of TM and SPOT images[J]. Remote Sensing Technology and Application (in Chinese),2001,16(2):110-115.

[6] Liu J G. Smoothing Filter-based Intensity Modulation:a Spectral Preserve Image Fusion Technique for Improving Spatial Details[J]. International Journal of Remote Sensing,2000,21(18):3461-3472

[7] Li Junjie, He Longhua,Dai Jinfang. Analysis of Pixel-level Remote Sensing Image Fusion Methods[J].Geo-information Science (in Chinese),2008,10(1):128-134.

[8] Xu Han-qiu. Study on Data Fusion and Classification of Landsat 7 ETM+ Imagery[J]. Journal of Remote Sensing(in Chinese),2005,9(2):186-194.