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An improved IHS fusion method of GF-2 remote sensing images

机译：GF-2遥感图像的改进IHS融合方法

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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.
机译：IHS变换融合是图像融合最广泛使用的技术之一。但是，IHS变换融合带来了光谱失真。为了开发新的图像融合方法，有必要研究来自不同传感器的原始图像的光谱特征。在该研究中，重建高分辨率的平面图像以改善基于GF-2卫星图像的IHS变换。使用NSCT变换以分离细节和光谱信息。提出了用于评估富力度的合成指数（SI），考虑到平均梯度，熵，相关系数和光谱失真。结果表明，在城市地区，改进的IHS方法的SI从2.75增加到4.30，杂种方法的SI（改进的IHS + NSCT方法）从6.68增加到6.93。此外，所提出的方法有助于将1.10到3.80的Si从6.00到3.46改善为植被覆盖区域。因此，改进的IHS变换将保持光谱保真度并显着改善植被光谱信息。

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