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Remote Sensing Image Fusion Using Improved IHS and Non-subsampled Contourlet Transform
Low-altitude security monitoring and spatial visualization can make use of high spatial resolution remote sensing images, and pixel-level image fusion techniques can be used to combine panchromatic and multispectral images to generate composite images with high resolution and rich spectral information. The IHS transform fusion is one of the most widely used techniques for image fusion. However, the IHS transform fusion brings spectral distortion. In order to develop new image fusion methods, it is necessary to investigate the spectral features of the original images from different sensors. In this study, high-resolution panchromatic images were reconstructed to improve IHS transform based on GF-2 satellite images. The NSCT transform was used in order to separate details and spectral information. A synthetic index (SI) for assessing fidelity was proposed with consideration of average gradient, entropy, correlation coefficient, and spectral distortion. Results show that, in urban areas, the SI of improved IHS method increases from 2.75 to 4.30, and the SI of the hybrid method (improved IHS + NSCT method) increases from 6.68 to 6.93. In addition, the proposed method helps to improve the SI from 1.10 to 3.80 and the NSCT from 6.00 to 7.46 for vegetation-covered areas. Thus, the improved IHS transform would maintain spectral fidelity and significantly improve the vegetation spectral information.
Remote Sensing Image Fusion Using Improved IHS and Non-subsampled Contourlet Transform
Low-altitude security monitoring and spatial visualization can make use of high spatial resolution remote sensing images, and pixel-level image fusion techniques can be used to combine panchromatic and multispectral images to generate composite images with high resolution and rich spectral information. The IHS transform fusion is one of the most widely used techniques for image fusion. However, the IHS transform fusion brings spectral distortion. In order to develop new image fusion methods, it is necessary to investigate the spectral features of the original images from different sensors. In this study, high-resolution panchromatic images were reconstructed to improve IHS transform based on GF-2 satellite images. The NSCT transform was used in order to separate details and spectral information. A synthetic index (SI) for assessing fidelity was proposed with consideration of average gradient, entropy, correlation coefficient, and spectral distortion. Results show that, in urban areas, the SI of improved IHS method increases from 2.75 to 4.30, and the SI of the hybrid method (improved IHS + NSCT method) increases from 6.68 to 6.93. In addition, the proposed method helps to improve the SI from 1.10 to 3.80 and the NSCT from 6.00 to 7.46 for vegetation-covered areas. Thus, the improved IHS transform would maintain spectral fidelity and significantly improve the vegetation spectral information.
Remote Sensing Image Fusion Using Improved IHS and Non-subsampled Contourlet Transform
Stud. in Distributed Intelligence
Yuan, Xiaohui (editor) / Elhoseny, Mohamed (editor) / Zeng, Yong (author) / Yi, Wei (author) / Deng, Jianan (author) / Chen, Weirong (author) / Xu, Shenghao (author) / Huang, Shusong (author)
2020-06-26
13 pages
Article/Chapter (Book)
Electronic Resource
English
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