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基于Keren配准和插值的快速超分辨率图像重建 被引量:7

Fast Super-Resolution Image Reconstruction Based on Keren Registration and Interpolation
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摘要 为提高图像超分辨率重建技术实时应用的可能性,增强其对配准误差的容忍度,提出了一种基于Keren配准和插值的快速鲁棒超分辨率图像重建算法.该算法将配准后的低分辨率图像根据变换参数映射到高分辨率网格上,再利用模板卷积迭代地填充缺失像素值,从而重建一幅高分辨率图像.将文中算法与非均匀插值法、凸集映射法、鲁棒的迭代后向映射法和结构适应的归一化卷积法4种超分辨率图像重建算法进行了比较.实验结果表明,文中算法对一定精度范围内的配准误差不敏感,在速度和重建效果上具有一定的优势,是一种有效、鲁棒和快速的多帧超分辨率图像重建算法. In order to make it possible to apply the super-resolution reconstruction(SRR) technology of images in real time and to improve the tolerance of registration errors,a fast and robust SRR algorithm based on Keren registration and interpolation is proposed.In this algorithm,registered low-resolution(LR) images are mapped onto a high-resolution(HR) grid according to their transform parameters,and the space pixels are filled iteratively via the template convolution to reconstruct a HR image.The proposed algorithm is finally compared with four existing SRR algorithms including the nonuniform interpolation,the projection onto convex sets,the robust iterative back projection and the structure-adaptive normalized convolution.The results show that the proposed algorithm is an effective,robust and fast SRR method for multi-frame images because it is insensitive to registration errors in a certain accuracy range with high reconstruction speed and quality.
出处 《华南理工大学学报(自然科学版)》 EI CAS CSCD 北大核心 2011年第5期84-90,共7页 Journal of South China University of Technology(Natural Science Edition)
基金 国家自然科学基金资助项目(10778617 10973007 61070090) 广东省科技计划重大专项(2010A080402005) 广东省科技计划项目(2008B080701052 2010B080701062) 广东省自然科学基金资助项目(10151063201000002)
关键词 图像重建 超分辨率 Keren配准 插值 卷积 image reconstruction super resolution Keren registration interpolation convolution
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参考文献21

  • 1Park S C,Park M K,Kang M G.Super-resolution image reconstruction:a technical overview[J].IEEE Signal Processing Magazine,2003,20(3):21-36.
  • 2Tsai R Y,Huang T S.Multiframe image restoration and registration[J].Advances in Computer Vision and Image Processing,1984,1 (2):317-339.
  • 3Stark H,Oskoui P.High resolution image recovery from image-plane arrays,using convex projections[J].Journal of the Optical Society of American,1989,6 (1 1):1715-1726.
  • 4Kim S,Bose N K,Valenzuela H.Recursive reconstruction of high resolution image from noisy undersampled multiframes[J].IEEE Transactions on Acoustics,Speech,and Signal Process,1990,38 (6):1 013-1027.
  • 5Irani M,Peleg S.Improving resolution by image registration[J].Computer Vision,Graphics and Image Processing,1991,53 (3):231-239.
  • 6Schultz R R,Stevenson R L.Extraction of high-resolution frames from video sequences[J].IEEE Transactions on Image Processing,1996,5 (6):996-1011.
  • 7Zomet A,Rav-Acha A,Peleg S.Robust super-resolution[C] //Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Hawaii:IEEE,2001:645-650.
  • 8Elad M,Feuer A.Restoration of a single superresolution image from several blurred,noisy,and undersampled measured images[J].IEEE Transactions on Image Processing,1997,6 (12):1646-1658.
  • 9Pham T Q,van Vliet L J,Schutte K.Robust fusion of irregularly sampled data using adaptive normalized convolution[J].EURASIP Journal on Applied Signal Processing,2006,2006(10):236-247.
  • 10Datsenko D,Elad M.Example-based single document image super-resolution:a global MAP approach with outlier rejection[J].Multidimensional System and Signal Processing,2007,18(2):103-121.

二级参考文献19

  • 1范冲,龚健雅,朱建军.一种基于去混叠影像配准方法的POCS超分辨率序列图像重建[J].测绘学报,2006,35(4):358-363. 被引量:12
  • 2Park S C, Park M K, and Kang M G. Super-resolution image reconstruction: A technical overview [J]. IEEE Signal Processing Magazine, 2003, 20(3): 21-36.
  • 3Farsiu S, Robinson D, Elad M, and Milanfar P. Advances and challenges in super-resolution [J]. International Journal of Imaging Systems and Technology, 2004, 14(2): 47-57.
  • 4Nguyen N, Milanfar P, and Golub G. A computationally efficient superresolution image reconstruction algorithm [J].IEEE Trans. on Image Processing, 2001, 10(4): 573-583.
  • 5Schultz R R and Stevenson R L. Extraction of high-resolution frames from video sequences [J]. IEEE Trans. on Image Processing, 1996, 5(6): 996-1011.
  • 6Patti A J, Sezan M I, and Tekalp A M. Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time [J]. IEEE Trans. on Image Processing, 1997, 6(8): 1064-1076.
  • 7Han Yubing and Wu Lenan. Super resolution reconstruction of video sequence based on total variation [C]. International Symposium on Intelligent Multimedia Video and Speech Processing, Hongkong, 2004: 575-578.
  • 8Ayers G R and Dainty J C. Iterative blind deconvolution method and its applications [J]. Optics Letters, 1988, 13(7): 547-549.
  • 9Capel D P. Image Mosaicing and Super-Resolution [M]. London: Springer-Verlag, 2004, Chapter 3.
  • 10T. S. Huang,R. Y. Tsay. Multiple frame image restoration and registration[J]. Advances in Computer Vision and Image Processing,1984,1(2):317-339.

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