@article{CAO2023, 
author = {Shengfang CAO and Hongping HU and Wenke WANG},
title = {Blind image deblurring method based on l1/l2-norm regularization},
year = {2023},
journal = {Journal of Measurement Science and Instrumentation},
volume = {14},
number = {2},
pages = {182-188},
keywords = {blind image deblur, regularization, fast iterative contraction threshold, fast Fourier transform},
url = {https://www.sciopen.com/article/10.62756/jmsi.1674-8042.2023021},
doi = {10.62756/jmsi.1674-8042.2023021},
abstract = {Aiming at the problem of ringing artifacts existing in the edge of image in traditional blind image deblurring methods, l1/l2 regularization-based blind image deblurring method is proposed. The latent image is constrained by l1/l2 regularization, and the two-norm constraint is applied to the blur kernel to remove the noise of the blur kernel. During the solution process, the latent image and the blur kernel are updated alternately anditeratively, and the deblur redimage is finally obtained by combining the finest estimated blur kernel with the non-blind deblurring method. The experimental results show that the proposed method improves the quality of image deblurring and effectively removes some ringing artifacts. It has a good restoration effect on natural blurred images.}
}