基于高斯曲率和加权图总变分正则化的遥感图像盲去模糊算法

doi:10.13229/j.cnki.jdxbgxb.20230140

Abstract

Abstract:

To tackle the motion blur in the process of acquiring remote sensing images， an algorithm for blind deblurring of remote sensing images is designed. The algorithm is based on the geometric property of image surfaces and the algebraic property of image pixels， and it utilizes Gaussian curvature and reweighted graph total variation. First， the reweighted graph total variational prior and Gaussian curvature prior were combined to obtain the skeleton image which not only retains the gradient and sharp edge information， but also removes the harmful structural information in the latent clean image. Then， the skeleton image is used to estimate the fuzzy kernel， and then the non-blind deblurring algorithm is used to obtain the clear image. Finally, simulation validation was conducted on 8 fuzzy remote sensing images in different scenarios, and the results showed that, compared with other advanced image deblurring algorithms， the peak signal-to-noise ratio of the recovery effect of the deblurring algorithm proposed is higher than that of the comparison algorithm by 2.76， 1.84， 3.11， 2.79， 3.35， 2.76 dB， respectively. The structure similarity is higher than that of the comparison algorithm by 0.0792、0.0604、0.0873、0.0801、0.0997、0.0906， respectively. The remote sensing images recovered by our proposed algorithm have clear edge contours and local details while improving the clarity of remote sensing images.

Key words: computational mathematics, remote sensing image, Gaussian curvature, reweighted graph total variation, blind image deblurring

CLC Number:

TP751

Zhi-dan CAI,Ming FANG,Zhe LI,Jia-lu XU. Blind remote sensing image deblurring algorithm based on Gaussian curvature and reweighted graph total variation[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(9): 2649-2658.

Figures/Tables 8

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图像	文献［11］		文献［22］		文献［15］		文献［14］		文献［23］		文献［18］		本文算法
图像	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
海滩	36.21	0.9596	37.43	0.9621	34.84	0.9534	35.27	0.9558	34.61	0.9518	36.86	0.9620	37.45	0.9634
沙漠	34.15	0.9936	34.24	0.9939	34.23	0.9936	34.34	0.9938	33.97	0.9934	35.48	0.9950	35.49	0.9950
学校	22.25	0.8122	22.03	0.7903	21.75	0.7933	21.47	0.7849	22.41	0.8147	21.80	0.7840	25.59	0.8775
度假村	18.75	0.6046	21.96	0.7186	18.87	0.6090	18.49	0.5924	16.35	0.4946	18.32	0.5849	22.03	0.7209
机场	26.59	0.8785	25.97	0.8453	26.74	0.8819	27.81	0.9002	27.13	0.8876	25.78	0.8618	27.86	0.8901
山地	15.45	0.4885	15.50	0.4648	15.08	0.4823	15.49	0.4914	15.53	0.4900	15.99	0.4948	20.27	0.7045
广场	20.64	0.7387	22.39	0.7696	20.56	0.7337	20.92	0.7479	20.12	0.7197	20.15	0.7148	25.05	0.8587
高架桥	24.94	0.6236	26.85	0.7047	24.11	0.5873	24.97	0.6253	24.16	0.5831	24.62	0.6110	27.34	0.7226

Blind remote sensing image deblurring algorithm based on Gaussian curvature and reweighted graph total variation

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