Learning from Ideal Edge for Image Restoration-Reference-Cited by-同舟云学术

Learning from Ideal Edge for Image Restoration

Published:2013 Issue:11 Volume:E96.D Page:2487-2491
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

HE Jin-Ping¹,GAO Kun²,NI Guo-Qiang²,SU Guang-Da³,CHEN Jian-Sheng³

Affiliation:

1. Beijing Institute of Space Mechanics & Electricity

2. School of Optoelectronics, Beijing Institute of Technology

3. Department of Electronics Engineering, Tsinghua University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E96.D/11/E96.D_2487/_pdf

Reference10 articles.

1. [1] R.L. Lagendijk and J. Biemond, “Block-adaptive image identification and restoration,” Proc. ICASSP, vol.4, pp.2497-2500, 1991.

2. [2] H. Kaufman and A.M. Tekalp, “Survey of estimation techniques in image restoration,” IEEE Control Syst. Mag., vol.11, pp.16-24, 1991.

3. [3] M.J. Wahoske, R.-W. Liu and R.L. Stevenson, “Dual-receiver blind identification for image blurs,” IEEE International Symposium on Circuits and Systems, vol.2, pp.1377-1380, 1997.

4. [4] J. Biemond, F.G. Van der Putten, and J.W. Woods, “Identification and restoration of images with symmetric noncausal blurs,” IEEE Trans. Circuits Syst., vol.358, pp.385-393, 198.

5. [5] M.-Y. Zou, “Deconvolution and Signal Recovery,” National Defence Industry Press., Beijing, 2001.

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