| Environmental Engineering |
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| Multi-spectral remote sensing image enhancement method based on PCA and IHS transformations |
| Shan-long Lu, Le-jun Zou, Xiao-hua Shen, Wen-yuan Wu, Wei Zhang |
| Department of Earth Sciences, Zhejiang University, Hangzhou 310027, China, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China, China Aero Geophysical Survey & Remote Sensing Center for Land and Resources, Beijing 100083, China |
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Abstract This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery, based on principal component analysis (PCA) and intensity-hue-saturation (IHS) transformations. The PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component, respectively. The enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation, and undertaking the inverse IHS transformation. The objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral image. On the basis of the visual and statistical analysis results of the experimental study, we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color distortion. It has potential advantages in image mapping optimization, object recognition, and weak information sharpening.
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Received: 14 June 2010
Published: 07 June 2011
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