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一种基于分形码和模型约束的图像放大算法 被引量:11

Image Magnification Based on Fractal Codes and Model Constraint
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摘要 图像放大技术在众多研究领域中有着重要的应用.本文提出一种基于分形码和模型约束的图像放大算法,分形码能够包含图像的空间信息和图像本身的自相似信息,模型约束能够有效的限制放大引入的误差.我们首先对图像采用多种值域块分割方案计算得到多组分形码,并由此得到多个放大图像,然后对放大图像进行平均,从而降低编码误差,最后采用约束模型对放大图像进行修正.实验结果表明,利用本文的方法可以大大提高放大图像的PSNR. Image magnification plays an important role in many fields. An algorithm based on fractal codes and model constraint is proposed in this paper. The fractal codes can carry the spatial information as well as the self-similarities present in the image. First,the image is magnified with multiple range block partition schemes,then their results are averaged to get one magnification image and thus the block artifact is reduced. Finally, the magnification image is modified by a constrained model. Experiments show that the proposed approach performs better than the other fractal based magnification method.
出处 《电子学报》 EI CAS CSCD 北大核心 2006年第3期433-436,共4页 Acta Electronica Sinica
基金 北京市自然科学基金 北京市教委重点项目(No.KZ200310005004) 国家自然科学基金(No.60431020No.60472036)
关键词 图像放大 分形编码 模型约束 image magnification fractal coding model constraint
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参考文献12

  • 1W K Pratt.Digital Image Processing[M].New York,USA:John Wiley & sons,INC,2001.393-297.
  • 2M Unser.Splines:a perfect fit for signal and image processing[J].IEEE Signal Processing Magazine,1999,16 (6):22 -38.
  • 3R R Schultz,R L Stevenson.A bayesian approach to image expansion for improved definition[J].IEEE Trans Image Processing,1994,3 (3):233-242.
  • 4W K Carey,D B Chuang,S S Hemami.Regularity preserving image Interpolation[J].IEEE Trans Image Processing,1999,8 (9):1293-1297.
  • 5S Chaudhuri.Super-resolution imaging[M].Boston:Kluwer Academic Publishers,2001.21 -44.
  • 6Barsley.Fractals everywhere[M].New York:Academic Press,1988.
  • 7Y Fisher.Fractal image compression:theory and application[M].Berlin,Germany:Springer-Verlag,1995.
  • 8A E Jacquin.Fractal image coding:a review[J].Proc IEEE,1993,81 (10):1451-1465.
  • 9S K Mitra,C A Murthy,M K Kundu.A technique for image magnification using partitioned iterative function system[J].Pattern recognition,2000,33 (7):1119 -1133.
  • 10K H Chung,Y H Fung,Y H Chan.Image enlargement using fractal[J].IEEE International Conference on Coustics,Speech,and Signal Processing,2003,6:6 -10.

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  • 2朱宁,吴静,王忠谦.图像放大的偏微分方程方法[J].计算机辅助设计与图形学学报,2005,17(9):1941-1945. 被引量:49
  • 3黄华,樊鑫,齐春,朱世华.基于识别的凸集投影人脸图像超分辨率重建[J].计算机研究与发展,2005,42(10):1718-1725. 被引量:8
  • 4韩玉兵,吴乐南.基于自适应滤波的视频序列超分辨率重建[J].计算机学报,2006,29(4):642-647. 被引量:14
  • 5Park S C, Park M K, and Kang M G. Super-resolution image reconstruction: A technical review [J]. [EEE Signal Processing Magazine, 2003, 20(3): 21-36.
  • 6Hardie Russell C, Barnard Kenneth J, and Bognar John G, et al.. High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system [J]. Optical Engineering, 1998, 37(1) 247-260.
  • 7Blerling M and Thema R. Motion compensating field interpolation using a hierarchically structured displacement estimator [J]. Signal Processing, 1986, 11(4): 387-404.
  • 8Patanavijit V and Jitapunkul S. An iterative superresolution reconstruction of image sequences using a bayesian approach with BTV prior and affine block-based registration [C]. The 3rd Canadian Conference on Computer and Robot Vision(CRV'06), 'Quebec City, June 7-9, 2006: 45-51.
  • 9Barreto D, Callico G M, and Lopez S, et al.. Real-time super-resolution over raw video sequences [J]. Proceedings of SPIE, Vol.5837 VLSI Circuits and Systems II, 2005: 628-637.
  • 10李弼程,彭天强,彭波等.智能图像处理技术[M].北京:电子工业出版社,2005:260-290.

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