Fast variational detection of stripe noise based on interval sampling

BAI Yuchuan; XU Rui; LI Zongrui; PAN Jun

doi:10.6046/zrzyyg.2022161

2023 Vol. 35, No. 3

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BAI Yuchuan, XU Rui, LI Zongrui, PAN Jun. 2023. Fast variational detection of stripe noise based on interval sampling. Remote Sensing for Natural Resources, 35(3): 71-79. doi: 10.6046/zrzyyg.2022161

Citation:

BAI Yuchuan, XU Rui, LI Zongrui, PAN Jun. 2023. Fast variational detection of stripe noise based on interval sampling. Remote Sensing for Natural Resources, 35(3): 71-79. doi: 10.6046/zrzyyg.2022161

Fast variational detection of stripe noise based on interval sampling

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received Date: 22 April 2022

Revised Date: 04 January 2023

Publish Date: 19 September 2023

Abstract

Abstract

This study proposed a fast variational detection method for stripe noise based on interval sampling, aiming to improve the detection efficiency of multi-column strip noise during the pushbroom imaging of mainstream satellites. Based on the variational modeling of stripe noise components and the optimal solution, this method can quickly determine stripe noise components through interval sampling and establishing an estimation model of stripe noise components with interval sampling parameters. Then, this method can locate the stripe noise through the one-dimensional outlier detection and post-processing of the column mean values of stripe noise components. Owing to the interval sampling strategy, the method proposed in this study significantly improves the detection efficiency without impairing the stripe noise detection accuracy.
- strip noise /
- variational model /
- automatic detection