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Proceedings Paper

A restoration method for the turbulent degraded images based on the salient edge selection and the L0 norm constraint
Author(s): Yayuan Feng; Yu Shi; Dianjun Sun; Meixuan Wang
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Paper Abstract

At present, the restoration of turbulent degraded images is a worldwide problem in the fields of astronomical imaging. Atmospheric turbulence is the reason why images will be blurred, which gravely interferes the object of recognition and the detection of images. This paper presents a restoration method for the turbulent degraded images based on the image saliency edge selection and the L0 norm constraint, which aims to recover sharp images from the turbulent degraded images. The proposed method imposes the L0 norm sparse constraint on the latent image, and uses the method of split Bregman to solve the problem of optimization. To avoid the influence of the tiny details on the point spread function (PSF) , we use the image saliency algorithm to build a weighted model to select salient edges from the latent images. Based on the salient edge in the gradient domain, the proposed method establishes an estimation model of the point spread function. The calculation part of the point spread function is solved accurately by using the fast Fourier transform (FFT) in the frequency domain. The proposed method uses the multi-scale pyramid strategy to alternatively solve the point spread function and the latent images, which can obtain the final accuracy of the point spread function.

Paper Details

Date Published: 14 February 2020
PDF: 6 pages
Proc. SPIE 11428, MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis, 114280G (14 February 2020); doi: 10.1117/12.2536579
Show Author Affiliations
Yayuan Feng, Hubei Key Lab. of Optical Information and Pattern Recognition (China)
Hubei Engineering Research Ctr. of Video Image and High Definition Projection (China)
Wuhan Institute of Technology (China)
Yu Shi, Hubei Key Lab. of Optical Information and Pattern Recognition (China)
Hubei Engineering Research Ctr. of Video Image and High Definition Projection (China)
Wuhan Institute of Technology (China)
Dianjun Sun, Hubei Key Lab. of Optical Information and Pattern Recognition (China)
Hubei Engineering Research Ctr. of Video Image and High Definition Projection (China)
Wuhan Institute of Technology (China)
Meixuan Wang, 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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