Study on Fusion Algorithms of GF-2 Satellite Image

doi:10.16182/j.issn1004731x.joss.201711020

Abstract

Abstract: This paper compared 4 kinds of image fusion methods through the GF-2 panchromatic and multispectral data fusion test. The subjective qualitative evaluation and objective quantitative evaluation were applied to analyze the quality of the fusion images, which were classified by the maximum likelihood method to select the suitable fusion method for GF-2 image. Test results showed that, among the four fusion methods, Pansharp transform achieved better fusion effect. It had the best subjective and objective qualitative evaluation; It had the highest overall classification accuracy in the maximum likelihood classification test. The experiment results indicated that the Pansharp transform had better fusion effect than other fusion algorithms, and it was suitable for the application of GF-2 in forestry industry. The research aimed to provide reference for the application of image fusion in the forestry sector.

Key words: image fusion, GF-2 satellite image, evaluating indicator, image quality, image classification

CLC Number:

TP751

Xie Shiqin, Zhao Tianzhong, Wang Wei, Shi Jingjing. Study on Fusion Algorithms of GF-2 Satellite Image[J]. Journal of System Simulation, 2017, 29(11): 2742-2747.

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