Band registration method of hyperspectral data based on linear progressive filter imaging

doi:10.7523/j.ucas.2021.0077

Abstract

Abstract: As a new type of sensor, the hyperspectral data processing principle of linear progressive filter imaging sensor is different from that of traditional linear array hyperspectral data, and the related research is scarce. When the traditional method is used in image registration of this new type data, the accuracy of image registration is not high. Aiming at the problem of geometric correction of linear progressive filtering hyperspectral images, this paper proposes a band registration strategy of grouping return registration and an image registration algorithm based on improved SIFT algorithm (DS-SIFT algorithm). DS-SIFT algorithm includes rough registration and precise registration. The precise registration is based on the improved SIFT algorithm of block, which can improve the registration accuracy and efficiency between different bands by introducing information entropy and structural similarity for the search of image blocks. The flight data were used to verify the algorithm, and the results show that the proposed process can obtain high quality hyperspectral registration data.

Key words: linear progressive filter imaging, geometric correction, registration, DS-SIFT

CLC Number:

P237

YU Chunyao, FANG Junyong, WANG Xiao, ZHANG Xiaohong, LIU Xue. Band registration method of hyperspectral data based on linear progressive filter imaging[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(3): 406-414.

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