@inproceedings{5a7006f96c3a4fe7994867c1c87d4106,
title = "Improved curvelet thresholding algorithm for astronomical image denoising",
abstract = "In image denoising, in order to overcome the shortcoming that the uniform wavelet threshold in iterative thresholding algorithm can't separate the image from noise effectively at each iteration leads to the quality of the reconstructed image is poor, an improved curvelet threshold is proposed to replace it. And then iterative curvelet thresholding algorithm based on the improved threshold is proposed. In this paper, we apply the proposed algorithm for high resolution astronomical image denoising. The experimental result shows that the proposed algorithm improves the visual quality, effectively protects astronomical image details. When compression ratio is lower, the proposed algorithm still can obtain a higher peak signal to noise ratio (PSNR).",
keywords = "Astronomical image, Curvelet threshold, Denoising, Wavelet threshold",
author = "Jie Zhang and Xiaoping Shi and Hailong Liu",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 ; Conference date: 03-10-2016 Through 05-10-2016",
year = "2017",
month = feb,
day = "28",
doi = "10.1109/IMCEC.2016.7867269",
language = "英语",
series = "Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "539--542",
editor = "Bing Xu",
booktitle = "Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016",
address = "美国",
}