Generalized IHS-BT framework for the pansharpening of high-resolution satellite imagery

Chih-Bin Hsu; Jen-Chun Lee; Te-Ming Tu

doi:10.1117/1.JRS.12.046008

19 October 2018 Generalized IHS-BT framework for the pansharpening of high-resolution satellite imagery

Chih-Bin Hsu, Jen-Chun Lee, Te-Ming Tu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 046008 (October 2018). https://doi.org/10.1117/1.JRS.12.046008

Abstract

Image fusion is an important technique for enhancing the spatial resolution of multispectral imagery by merging with a corresponding high-resolution panchromatic image. Many algorithms have been developed to obtain a better trade-off between spectral fidelity and spatial resolution enhancement. The recently developed techniques use sophisticated algorithms; however, three issues are often ignored. The first involves the progressively increasing amount of high-resolution satellite image data. Second, the designed method needs to be versatile to process a variety of complex terrain and surface features. The third is that the proposed method must satisfy the requirements of both visual inspection and classification. Based on the previous studies, this work proposes a generalized intensity–hue–saturation and Brovey transform framework (GF) to tackle these three problems. Eight modules are integrated into this GF: four modules are designed for classification with a new intensity matching technique to improve the spectral quality; the other four modules are the spatial-enhancement version for visual inspection by adding more native spatial details. To verify the proposed technique, the experiments are conducted for QuickBird and WorldView-2 images. The results show that the GF modules can offer the maximal spatial information content while preserving good spectral information quality.

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Chih-Bin Hsu, Jen-Chun Lee, and Te-Ming Tu "Generalized IHS-BT framework for the pansharpening of high-resolution satellite imagery," Journal of Applied Remote Sensing 12(4), 046008 (19 October 2018). https://doi.org/10.1117/1.JRS.12.046008

Received: 12 April 2018; Accepted: 28 September 2018; Published: 19 October 2018

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