Comparative analysis of fusion models based on remote sensing applications

Ying Zhang; Binbin He; Xiaowen Li

doi:10.1117/12.832813

30 October 2009 Comparative analysis of fusion models based on remote sensing applications

Ying Zhang, Binbin He, Xiaowen Li

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74982X (2009) https://doi.org/10.1117/12.832813
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

The evaluation of performances of fusion methods is a key problem in remote sensing image fusion. In this paper, four representative fusion methods, PCA fusion, WT fusion, CT fusion and TLS-GIF-WC, are adopted to fuse two sets of ALI images for comparison. The fusion products are applied to two remote sensing applications, vegetation index extraction and image classification. The normalized difference vegetation index (NDVI), vegetation coverage and classification accuracy indices are adopted to compare the fusion products. Experiments show that the GIF fusion products are more adaptive for vegetation application, since the NDVI and vegetation coverage extracted from the fusion product are consistent with that extracted from the initial image, and the ARSIS concept fusion and TLS-GIF-WC products are more adaptive for image classification, because of the higher classification accuracy.

Citation Download Citation

Ying Zhang, Binbin He, and Xiaowen Li "Comparative analysis of fusion models based on remote sensing applications", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74982X (30 October 2009); https://doi.org/10.1117/12.832813

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