The method based on L1 norm optimization model for stripe noise removal of remote sensing image

Kai LI; Wen-Li LI; Chang-Pei HAN

doi:10.11972/j.issn.1001-9014.2021.02.018

Journal of Infrared and Millimeter Waves, Volume. 40, Issue 2, 272(2021)

The method based on L1 norm optimization model for stripe noise removal of remote sensing image

Kai LI^1,2,3, Wen-Li LI^1,2,3, and Chang-Pei HAN^1,2、*

Author Affiliations

¹Shanghai Institute of Technical Physics，Chinese Academy of Sciences，Shanghai 200083，China

²Key Laboratory of Infrared Detection and Imaging Technology，Chinese Academy of Sciences，Shanghai 200083，China

³University of Chinese Academy of Sciences，Beijing 100049，China

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Figures & Tables(19)

Fig. 1. The framework of the proposed model

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Fig. 2. (a) The original remote sensing image, (b) weighting factor image in Eq. 8, (c) the smooth part, (d) the high frequency part, (e) weighting factor image in Eq. 9, (f) edge weighting image in Eq. 10

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Fig. 3. Destriped results of AGRI band 11 subimage (a) original image, (b) WFAF, (c) SLD, (d) UTV, (e) proposed method

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Fig. 4. Mean line profiles for images shown in Fig. 3, (a) WFAF, (b) SLD, (c) UTV, (d) proposed method

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Fig. 5. Column-averaged power spectrum for images shown in Fig. 3 (a) original image, (b) WFAF, (c) SLD, (d) UTV, (e) proposed method

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Fig. 6. Destriped results of AGRI band 11 subimage, (a) original image, (b) WFAF, (c) SLD, (d) UTV, (e) proposed method

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Fig. 7. The extracted stripe components of different algorithms (a) WFAF, (b) SLD, (c) UTV, (d) proposed method

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Fig. 8. Mean line profiles for images shown in Fig. 6 (a) WFAF, (b) SLD, (c) UTV, (d) proposed method

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Fig. 9. Column-averaged power spectrum for images shown in Fig. 6, (a) original image, (b) WFAF, (c) SLD, (d) UTV, (e) proposed method

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Fig. 10. (a) Reference image, (b) simulated stripe image

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Fig. 11. (a) The PSNR curve with $λ_{1}$ as independent variable, (b) The PSNR curve with $λ_{2}$ as independent variable

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Fig. 12. Processing results of different parameters $λ_{1}$

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Fig. 13. Processing results of different parameters $λ_{2}$

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Fig. 14. Destriping result of AGRI band 9 images with the proposed algorithm

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Fig. 15. Destriping result of AGRI band 10 images with the proposed algorithm

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Fig. 16. Destriping result of AGRI band 14 images with the proposed algorithm

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Table 1. The proposed destriping algorithm

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Table 1. The proposed destriping algorithm

1：Input：Stripe image f，parameters $λ_{1}$ ， $λ_{2}$ ， $β_{1}$ ， $β_{2}$ ， $β_{3}$ ， $δ$ and $S$ .
2：Initialize：Set $s^{0} = 0$ ， $Z^{0} = V^{0} = 0$ ， $H^{0} = \nabla_{y} f$ ， $p_{1} = 0$ ， $p_{2} = 0$ ， $p_{3} = 0$ ，and $ε = 10^{- 4}$ .
3：Solve $W_{f}$ by（10）
4：While $‖(f - s^{k}) - (f - s^{k - 1})‖ / ‖f - s^{k}‖ > ε$ and $k < N_{m a x}$ do
5：Solve $Z^{k + 1}$ ， $V^{k + 1}$ ， $H^{k + 1}$ using a thresholding method by（14），（17），（19）
6：Solve $s^{k + 1}$ using FFT by（21）
7：Update $p_{1}^{k + 1}$ ， $p_{2}^{k + 1}$ ，and $p_{3}^{k + 1}$ by（22）
8： End while
9：Output： $u^{k + 1} = f - s^{k + 1}$ .

Table 2. Spectral parameters

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Table 2. Spectral parameters

No.	Central Band /μm	Spectral Band /μm	Spatial Resolution	Number of pixels	Main Application
9	6.25	5.80∼6.70	4 km	4*1	upper-level water vapor
10	7.10	6.90∼7.30	4 km	4*1	mid-level water vapor
11	8.50	8.00∼9.00	4 km	4*1	integrated water vapor，cloud
14	13.50	13.20∼13.80	4 km	4*1	cloud，water vapor

Table 3. Qualitative results using NR, MRD and ID

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Table 3. Qualitative results using NR, MRD and ID

Image	Index	WFAF	SLD	UTV	Proposed
AGRI band 11 Periodical stripes noise	NR	10.06	10.78	12.93	13.67
	MRD（%）	1.781 7	0.734 2	4.033 4	0.875 1
	ID	0.987 8	0.999 9	0.857 0	0.998 4
AGRI band 14 Random stripe noise	NR	7.830 2	6.400 5	5.316 5	8.365 9
	MRD（%）	3.086 2	3.303 6	4.778 2	3.065 3
	ID	0.945 5	0.999 9	0.985 1	0.998 8

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Kai LI, Wen-Li LI, Chang-Pei HAN. The method based on L1 norm optimization model for stripe noise removal of remote sensing image[J]. Journal of Infrared and Millimeter Waves, 2021, 40(2): 272

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Paper Information

Category: Research Articles

Received: Apr. 26, 2020

Accepted: --

Published Online: Aug. 31, 2021

The Author Email: Chang-Pei HAN (changpei_han@mail.sitp.ac.cn)

DOI:10.11972/j.issn.1001-9014.2021.02.018

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