Abstract
The Gram-Schmidt spectral sharpening is one of the widely used image sharpening techniques with preserving the spectral information of images. It is a key step for selecting methods for simulating the low resolution pan image. In this paper, we compared the different select methods for low resolution pan applied to sharpening the GF-1 multispectral bands. The results indicated that the optimal GS sharpened GF-1 multispectral image was from the low resolution pan simulated from Lansat7 sensor. Although there was no significant difference between the ten sharpened images and the original low resolution multispectral images through visual inspection, the sharpening increase the correlation coefficients between the multispectral bands, which is not beneficial for land use classification. In the future, a comprehensive evaluation over more study areas with more images should be performed.
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Acknowledgment
This research work was jointly financially supported by the National Natural Science Foundation of China (Project No.41671422, 41661144030, 41561144012), the National Mountain Flood Disaster Investigation Project (SHZH-IWHR-57), the Innovation Project of LREIS (Project No.088RA20CYA, 08R8A010YA), and National Key Research and Development Project of China (2016YFC1402701). Thanks to China Center for Resources Satellite Data and Application for providing the GF-1 data.
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Liu, Q. (2020). Sharpening the Pan-Multispectral GF-1 Camera Imagery Using the Gram-Schmidt Approach: The Different Select Methods for Low Resolution Pan in Comparison. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_45
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