@inproceedings{5a33cf7f559b4287a0a8e1a3fda53463,
title = "An Improved Injection Model for Pansharpening Based on Weighted Least Squares",
abstract = "Pansharpening is a fusion technique to enhance the spatial resolution of multispectral images by combining with the panchromatic image. This problem can be formulated as detail extraction and injection model, thus the injection estimation is a key for fusion quality. In the literature, the regression-based models are extensively studied, where the solution is usually solved by the ordinary least squares method. To improve the accuracy and robustness of estimation, a new injection model based on weighted least squares is proposed in this paper. The weights are dependent on the local statistics of the input-output pairs, which enhance the regular area and suppress effect of outliers. Experimental results show that the proposed method outperforms the other state-of-the-art methods.",
keywords = "image fusion, multispectral image, pansharpening, remote sensing, weighted least squares",
author = "Yan Shi and Wei Wang and Aiyong Tan",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021 ; Conference date: 23-10-2021 Through 25-10-2021",
year = "2021",
doi = "10.1109/CISP-BMEI53629.2021.9624441",
language = "English",
series = "Proceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Qingli Li and Lipo Wang and Yan Wang and Wenwu Li",
booktitle = "Proceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021",
address = "United States",
}