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A maximum noise fraction transform with improved noise estimation for hyperspectral images

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Abstract

Feature extraction is often performed to reduce spectral dimension of hyperspectral images before image classification. The maximum noise fraction (MNF) transform is one of the most commonly used spectral feature extraction methods. The spectral features in several bands of hyperspectral images are submerged by the noise. The MNF transform is advantageous over the principle component (PC) transform because it takes the noise information in the spatial domain into consideration. However, the experiments described in this paper demonstrate that classification accuracy is greatly influenced by the MNF transform when the ground objects are mixed together. The underlying mechanism of it is revealed and analyzed by mathematical theory. In order to improve the performance of classification after feature extraction when ground objects are mixed in hyperspectral images, a new MNF transform, with an improved method of estimating hyperspectral image noise covariance matrix (NCM), is presented. This improved MNF transform is applied to both the simulated data and real data. The results show that compared with the classical MNF transform, this new method enhanced the ability of feature extraction and increased classification accuracy.

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Authors and Affiliations

  1. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, 100101, China

    Xiang Liu

  2. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, 100190, China

    Xiang Liu, Bing Zhang & LianRu Gao

  3. Queen’s University, Kingston, ON, K7L 3N6, Canada

    DongMei Chen

Authors
  1. Xiang Liu
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  2. Bing Zhang
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  3. LianRu Gao
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  4. DongMei Chen
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Corresponding author

Correspondence to Xiang Liu.

Additional information

Supported by the National Basic Research Program of China (Grant No. 2009CB723902), and the National High-Tech Research & Development Program of China (Grant No. 2007AA12Z138)

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Liu, X., Zhang, B., Gao, L. et al. A maximum noise fraction transform with improved noise estimation for hyperspectral images. Sci. China Ser. F-Inf. Sci. 52, 1578–1587 (2009). https://doi.org/10.1007/s11432-009-0156-z

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  • DOI: https://doi.org/10.1007/s11432-009-0156-z

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