[1]江静,张雪松.图像超分辨率重建算法综述[J].红外技术,2012,34(01):024-30.
 JIANG Jing,ZHANG Xue-song.A Review of Super-resolution Reconstruction Algorithms[J].Infrared Technology,2012,34(01):024-30.
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图像超分辨率重建算法综述
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
34卷
期数:
2012年01期
页码:
024-30
栏目:
出版日期:
2012-12-31

文章信息/Info

Title:
A Review of Super-resolution Reconstruction Algorithms
文章编号:
1001-8891(2012)01-0024-07
作者:
江静12张雪松3
1.华北科技学院 机电工程系,北京 101601;
2.中国矿业大学(北京)煤炭资源与安全开采国家重点实验室,北京 100083;
3.东北电子技术研究所 光电信息安全控制试验室,河北 三河 065201

Author(s):
JIANG Jing12ZHANG Xue-song3
1.Department of Mechanics and Electricity Engineering, North China Institute of Science and Technology, Beijing 101601, China;
2.State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China;
3.Electro-optical Information Security Control Laboratory, Northeast Institute of Electronics Technology, Sanhe Hebei 065201, China

关键词:
超分辨率重建规整化流形学习
Keywords:
Super-Resolution Reconstruction Regularization Manifold Learning Algorithm
分类号:
TP 391. 41
文献标志码:
A
摘要:
绍了超分辨率重建的基本原理与数学模型,对现有的图像超分辨率重建算法进行了总结。将当前的超分辨率算法分为基于重建约束的方法和基于学习的方法两大类,分别阐述了超分辨率重建技术的经典方法,最后指出了低质量图像超分辨率技术进一步的研究方向。
Abstract:
The basic principles and mathematical models of super-resolution reconstruction are described; the existing super-resolution reconstruction algorithms are summarized. The current super-resolution methods are divided into two categories, that is, the reconstructed constraints methods and learning approach. The methods of classic super-resolution reconstruction are respectively described. Finally, the further research directions of super-resolution reconstruction technique for low-quality images are proposed.

参考文献/References:

[1] ?Tsai R Y, Huang T S. Multiframe image restoration and registration. in Advances in Computer Vision and Image Processing: JAI Press Inc., 1984, 317-339.
[2] ?Kim S P, Bose N K, Valenzuela H M. Recursive reconstruction of high resolution image from noisy undersampled multiframes[J]. IEEE Trans. Acoust. Speech, Signal Processing, 1990, 38:1013-1027.
[3] ?Bose N K, Kim H C, Valenzuela H M. Recursive implementation of total least squares algorithm for image reconstruction from noisy, undersampled multiframes. Acoustics, Speech and Signal Processing, Minneapolis[C]//IEEE 1993, pp. 269-272.
[4] ?Rhee S H, Kang M G. Discrete cosine transform based regularized high-resolution image reconstruction algorithm. Opt. Eng., 1999, 38(8):1348-1356.
[5] ?John M. Wiltse, John L. Miller. Imagery improvements in staring infrared imagers by employing subpixel microscan[J]. Optical Engineering, 2005,44(5):056401-056409.
[6] ?Kim S P, Bose N K. Reconstruction of 2-d bandlimited discrete signals from nonuniform samples. Radar and Signal Processing[J]. IEE Proceedings Part F, 1990, 137(3):197-204.
[7] ?Katsaggelos A K. Digital image restoration. New York: Springer-Verlag, 1991.
[8] ?Schulz R R, Stevenson R L. Extraction of high-resolution frames from video sequences[J]. IEEE Trans. Image Processing, 1996, 5(6): 996-1011.
[9] ?Hardie R C, Barnard K J, Armstrong E E. Joint map registration and high-resolution image estimation using a sequence of undersampled images[J]. IEEE Transactions on Image Processing, 1997, 6(12): 1621-1633.
[10] ?Tom B C, Katsaggelos A K. Reconstruction of a high-resolution image by simultaneous registration, restoration, and interpolation of low-resolution images. Image Processing, Washington, DC[C]// IEEE 1995, 539-542.
[11] ?Stark H, Oskoui P. High resolution image recovery from image-plane arrays, using convex projections. J. Opt. Soc. Am. A, 1989, 6:1715-1726.
[12] ?Patti A J, Sezan M I, Tekalp A M. Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J]. IEEE Trans. Image Processing, 1997, 6(10):1064-1076.
[13] ?Irani M, Peleg S. Improving resolution by image registration. Graphical Models and Image Proc., 1991, 53(1): 231-239.

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备注/Memo

备注/Memo:
收稿日期:2011-11-01.
作者简介:江静(1979.6-),女,江苏省连云港市人,讲师,博士生(2008年于中国矿业大学(北京)在读通信与信息系统专业博士学位)。主要研究方向:模式识别与智能控制,超分辨率重建。主要研究成果:发明专利1项,实用新型专利1项,发表论文8篇等。E-mail: jiangjing@cumtb.edu.cn。?
基金项目:国家自然科学基金资助项目(51074169)、中央高校基本科研业务费资助(JD1201B)。

更新日期/Last Update: 2013-10-14