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Proceedings Paper

An accurate de-striping method based on cubic Hermite spline interpolation and gradient information of stripes
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Paper Abstract

Stripe is a common degradation phenomenon in remote sensing images. The variation-based de-striping method, due to the defect of the model itself, always has an unnecessary influence on the stripe-free area while correcting the stripe, and cannot satisfy some requirements in high-precision quantitative applications or sensitive data processing of remote sensing images. This paper proposes a high-precision stripe correction method, which first detects the position of the stripes, and then uses the interpolation idea to correct the stripe to solve the fidelity problem of the stripe-free area in the de-striping process. We use the rational assumption that the derivative of the real signal in the stripe region (to be repaired) is consistent with the derivative of the observed signal, and then selects cubic Hermite spline interpolation method for de-striping, which can uses the derivative information of the region to be repaired (ie, the derivative information of the stripe region) to overcoming the difficulty of the existing interpolation de-stripe method not being able to work well when the stripes is too wide. The experimental results show that our method can effectively remove the stripes and maintain the stripe-free area intact.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11428, MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis, 114280I (14 February 2020); doi: 10.1117/12.2538183
Show Author Affiliations
Yaozong Zhang, Wuhan Institute of Technology (China)
Hao Fang, Wuhan Donghu Univ. (China)
Zhenghua Huang, Wuhan Institute of Technology (China)
Zhengtao Li, Huazhong Univ. of Science and Technology (China)
Xiaoming Li, Beijing Thunisoft Information Technology Corp. Ltd. (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Hanyu Hong, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 11428:
MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Chao Pan; Hongshi Sang, Editor(s)

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