辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2014, Vol. 34 ›› Issue (2): 69-73.DOI: 10.3696/j.issn.1672-6952.2014.02.018

• 化工机械与计算机 • 上一篇    下一篇

基于重建方法的图像超分辨率技术发展现状分析与方向预测

卢紫微1,2,吴成东2   

  1. 1.辽宁石油化工大学计算机与通信工程学院,辽宁抚顺113001;2.东北大学信息科学与工程学院,辽宁沈阳110819
  • 收稿日期:2013-08-16 修回日期:2013-11-20 出版日期:2014-04-25 发布日期:2017-07-14
  • 作者简介:卢紫微(1981-),女,博士研究生,讲师,从事图像处理研究;E-mail:luziwei530@gmail.com。
  • 基金资助:
    国家自然科学基金资助项目(61273078)。

Current Status Analysis and Future Directions Prediction for Image SuperResolution Technique Based on Reconstructing Approach

Lu Ziwei1,2， Wu Chengdong2   

  1. （1. School of Computer and Communication Engineering, Liaoning Shihua University, Fushun Liaoning 113001,China; 2. School of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110819,China)
  • Received:2013-08-16 Revised:2013-11-20 Published:2014-04-25 Online:2017-07-14

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摘要： 图像超分辨率(superresolution,SR)重建技术是利用一帧或多帧低分辨率(lowresolution,LR)图像
的信息来重建一帧清晰的高分辨率(highresolution,HR)图像的技术,是图像处理中的研究热点。介绍了基于重建
方法的图像SR技术的基本原理及数学模型,以频域方法和空域方法作为分类依据,分别阐述了图像SR重建技术的
经典方法和最新进展,并对各类算法的优缺点进行了系统的分析和总结,最后指出了基于重建方法的图像SR技术
的研究方向。

关键词: 超分辨率 , 图像重建 , 对比分析 ,  图像处理 , 正则化

Abstract: Image superresolution(SR) reconstruction technique is how to produce a clearly high resolution(HR) image from the information of one or several low resolution(LR) images, and it has been received increasing attention from the image processing community. In the paper, the fundamental principles and mathematical models of SR technology based on reconstruction were described firstly, and the history and stateofart of image SR reconstruction were stated briefly according to the classification between the frequency domain method and the space domain method. Secondly, advantages and defects of different methods were analyzed and summarized systematically. Finally, the further research directions for image SR technique of reconstructing based the approach were proposed.

Key words: Superresolution, Image reconstruction, Comparative analysis, Image processing, Regularization　

引用本文

卢紫微,吴成东. 基于重建方法的图像超分辨率技术发展现状分析与方向预测[J]. 辽宁石油化工大学学报, 2014, 34(2): 69-73.

Lu Ziwei， Wu Chengdong. Current Status Analysis and Future Directions Prediction for Image SuperResolution Technique Based on Reconstructing Approach[J]. Journal of Liaoning Petrochemical University, 2014, 34(2): 69-73.

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