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ASSESSMENT OF THE SFIM ALGORITHM

XU Han-qiu

XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. 中国地理科学, 2004, 14(1): 48-56.
引用本文: XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. 中国地理科学, 2004, 14(1): 48-56.
XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. Chinese Geographical Science, 2004, 14(1): 48-56.
Citation: XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. Chinese Geographical Science, 2004, 14(1): 48-56.

ASSESSMENT OF THE SFIM ALGORITHM

基金项目: Under the auspices of the National Natural Science Foundation of China(No.40371107) and Ministry of Education of China
详细信息
    作者简介:

    XU Han-qiu(1955- ), male, a native of Jiangsu Province, Ph. D. of National University of Ireland, professor, specialized in remote sensing applications. E-mail: fdy@public.fz.fj.cn

  • 中图分类号: TP79;F301.24

ASSESSMENT OF THE SFIM ALGORITHM

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出版历程
  • 收稿日期:  2003-09-20
  • 刊出日期:  2004-03-20

ASSESSMENT OF THE SFIM ALGORITHM

    基金项目:  Under the auspices of the National Natural Science Foundation of China(No.40371107) and Ministry of Education of China
    作者简介:

    XU Han-qiu(1955- ), male, a native of Jiangsu Province, Ph. D. of National University of Ireland, professor, specialized in remote sensing applications. E-mail: fdy@public.fz.fj.cn

  • 中图分类号: TP79;F301.24

摘要: Fusion of images with different spatial and spectral resolutions can improve the visualization of the images. Many fusion techniques have been developed to improve the spectral fidelity and/or spatial texture quality of fused imagery. Of them, a recently proposed algorithm, the SFIM (Smoothing Filter-based Intensity Modulation), is known for its high spectral fidelity and simplicity. However, the study and evaluation of the algorithm were only based on spectral and spatial criteria. Therefore, this paper aims to further study the classification accuracy of the SFIM-fused imagery. Three other simple fusion algorithms, High-Pass Filter (HPF), Multiplication (MLT), and Modified Brovey (MB), have been employed for further evaluation of the SFIM. The study is based on a Landsat-7 ETM+ sub-scene covering the urban fringe of southeastern Fuzhou City of China.The effectiveness of the algorithm has been evaluated on the basis of spectral fidelity, high spatial frequency information absorption, and classification accuracy. The study reveals that the difference in smoothing filter kernel sizes used in producing the SFIM-fused images can affect the classification accuracy. Compared with three other algorithms, the SFIM transform is the best method in retaining spectral information of the original image and in getting best classification results.

English Abstract

XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. 中国地理科学, 2004, 14(1): 48-56.
引用本文: XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. 中国地理科学, 2004, 14(1): 48-56.
XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. Chinese Geographical Science, 2004, 14(1): 48-56.
Citation: XU Han-qiu. ASSESSMENT OF THE SFIM ALGORITHM[J]. Chinese Geographical Science, 2004, 14(1): 48-56.

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