@inproceedings{0996f2bd95f84319aa13778d1b3dd5e1,
title = "Parameter estimation for LP regularized image deconvolution",
abstract = "Parameter estimation in Total Variation (TV) deblurring has been extensively studied in the literature during the last decade. However, few works have been done for parameter estimation in ℓp (0 < p < 1) regularized image deconvo-lution, although ℓp outperforms TV and ℓ1 in natural image deblurring. In this paper, by utilizing the Bayesian framework, we propose an adaptive fast iteratively reweighted least squares algorithm for ℓp regularized image deconvolution, which automatically estimates the unknown image and regularization parameter. Experiments show that the proposed method yields nearly optimal results and outperforms the state-of-the-art methods.",
keywords = "Bayesian methods, Image restoration, adaptive, image deblurring, regularization parameter",
author = "Xu Zhou and Fugen Zhou and Xiangzhi Bai",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Image Processing, ICIP 2015 ; Conference date: 27-09-2015 Through 30-09-2015",
year = "2015",
month = dec,
day = "9",
doi = "10.1109/ICIP.2015.7351737",
language = "英语",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "4892--4896",
booktitle = "2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings",
address = "美国",
}