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- W4308791389 abstract "Over the past decades, land-cover classification has become a main topic in hyperspectral (HS) remote-sensing applications. HS image can achieve much higher classification accuracies and is able to recognize more categories. This chapter focuses on the collaborative classification of HS-centered multisource images, including HS image, high-resolution panchromatic, and long-wave infrared HS images. It reviews the current existing works of collaborative processing of multisource images and presents the main problems and challenges in multisource image collaborative processing. A comprehensive exploration of collaborative classification of multisource images is of great significance in enhancing the ability of data utilization and information acquisition, as well as the extension of the remote-sensing application. The chapter focuses on a decision level-based collaborative classification method for infrared HS and visible color images. High-resolution images usually present more ground details, thereby making the extraction of finer detailed spatial information possible." @default.
- W4308791389 created "2022-11-15" @default.
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- W4308791389 date "2022-11-11" @default.
- W4308791389 modified "2023-09-26" @default.
- W4308791389 title "Collaborative Classification Based on Hyperspectral Images" @default.
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- W4308791389 doi "https://doi.org/10.1002/9781119687788.ch18" @default.
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