Abstract Details
175 / 2023-11-26 21:16:21
WRONG
A
Draft Pending
This study addresses the issue of noise interference in hyperspectral images (HSI). By combining singular value decomposition (SVD) with an adaptive block algorithm, an improved algorithm for estimating noise intensity is proposed, aiming for precise assessment of noise levels. Additionally, an enhanced denoising method for hyperspectral images is introduced by integrating low-rank theory and sparse representation algorithms. The research results indicate that, for the Indian Pines public dataset, the denoising performance of the study surpasses existing algorithms by over 3.0 dB. Furthermore, robustness in estimating noise intensity is observed. Valuable insights for denoising similarly structured data with low signal-to-noise ratios are provided by this research, contributing meaningfully to the field.
Important Date
-
Conference Date
Nov 02
2023
toNov 04
2023
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Dec 15 2023
Draft paper submission deadline
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Dec 20 2023
Registration deadline
Sponsored By
IEEE Instrumentation and Measurement Society
Xidian University
Xidian University
Contact Information
Previous Conferences
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2025-11-21 China Guangzhou
2025 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence -
2023-11-02 China Xi'an
2023 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence -
2022-11-30 China Harbin
International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence -
2021-10-21 China Nanjing
2021 International Conference on Sensing, Measurement and Data Analytics in the era of Artificial Intelligence -
2020-10-15 China Xi'an
International Conference on Sensing, Measurement and Data Analytics in the era of Artificial Intelligence
