| Issue |
J. Eur. Opt. Soc.-Rapid Publ.
Volume 16, Number 1, 2020
|
|
|---|---|---|
| Article Number | 1 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1186/s41476-019-0123-2 | |
| Published online | 31 December 2019 | |
Research
Infrared stripe correction algorithm based on wavelet decomposition and total variation-guided filtering
1
Shenyang institute of automation, Chinese Academy of Sciences, 114, Nanta Street, Shenhe District, 110016, Shenyang, Liaoning, China
2
Key Laboratory of Optical Electrical Image Processing, Chinese Academy of Sciences, 114, Nanta Street, Shenhe District, 110016, Shenyang, Liaoning, China
3
College of automation and Electrical Engineering, Shenyang Ligong University, NO. 6 Nanping Middle Road, Hunnan District, 110159, Shenyang, Liaoning, China
Received:
6
August
2019
Accepted:
13
December
2019
Stripe non-uniformity severely affects the quality of infrared images. It is challenging to remove stripe noise in low-texture images without blurring the details. We propose a single-frame image stripe correction algorithm that removes infrared noise while preserving image details. Firstly, wavelet transform is used for multi-scale analysis of the image. At the same time, Total variation model is used for small window to smooth the original image. The small-scale total variation model can well preserve the edge information of the image, but it will leave stripe noise. Therefore, according to the prior knowledge of the vertical component of the stripe noise, the spatial filtering is finally performed: the smoothed image is used as the guide image for the stripe noise denoising. It is possible to prevent the lead filter from mistaking the strong stripe noise as edge detail, resulting in corrected image residual streak noise. The algorithm is systematically evaluated by experiments on simulated images and original infrared images, as well as compared with the current advanced infrared stripe non-uniformity correction algorithms. It is proved that our algorithm can better eliminate stripe noise and preserve edge details.
Key words: Focal-plane array;non-uniformity correction / Infrared image / Multi-scale / Destriping
© The Author(s) 2019
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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