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一种柔化锯齿的超分辨率图像重建方法 被引量:2

A Method of Softening the Jagged in Image Super-resolution Reconstruction
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摘要 基于锯齿会导致图像边缘长度增加的认识,通过减小边缘长度来抑制甚至消除图像锯齿,从而达到边缘锯齿被柔化的效果.受图像分割算法几何切的启发,首先提出一种新的图像边缘长度先验模型,该先验模型扩展了几何切的概念,使用全邻域系统,得到一种更具有实际意义的边缘长度的定义.然后把这个先验项连同图像似然项作为超分辨率图像重建的目标函数,并且通过最速下降法来极小化这个目标函数,从而达到减小边缘长度的目的.从实验结果可以看出该边缘长度先验模型具有一定的收敛性,并且边缘锯齿得到显著地柔化,图像变得更加地清晰,产生了良好的视觉效果. Based on the knowledge that the jagged will increase the length of edge,this paper suppressed or even eliminated the jagged by reducing the length of the image′s edge,so as to achieve the effect of softened jagged edges.Inspired by an image segmentation algorithm,the geometric cuts,this paper proposed a new priori model of the edge length firstly,which extended the concept of geometric cuts,used the whole neighborhood system,and got a more meaningful definition of the edge′s length.Then the priori term together with likelihood term formed the objective function of the image super-resolution reconstruction,and minimized by the steepest descent method,in order to achieve the purpose of reducing the length of the edges.Finally the results presented in this paper can show the convergence of the priori model,jagged edges are softened significantly,the images become more clearly,and have good visual effect.
出处 《厦门大学学报(自然科学版)》 CAS CSCD 北大核心 2012年第3期348-352,共5页 Journal of Xiamen University:Natural Science
基金 国防基础科研计划项目(B1420110155) 国防科技重点实验室基金
关键词 超分辨率 锯齿效应 边缘长度 几何切 super-resolution jagged effect edge length geometric cuts
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参考文献9

  • 1Baker S,Kanade T. Limits on super resolution and how to break them[J]. IEEE Trans Pattern Anal Mach Intell, 2002,24(9):1167-1183.
  • 2Patti A,Ahunbasak Y. Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and highe-order interpolants[J]. IEEE Trans actions on Image Processing,2001,10(1) :1167-1183.
  • 3Chantas G,Galatsanos N, Woods N. Super resolution b ased on fast registration and maximum a posteriori recon- struction[J]. IEEE Transactions on Image Processing, 2007,16(7) :1821-1830.
  • 4Sun Jian, Zhu Jiejie, Marshall F. Context-constrained hal- lucination for image super-resolution[C]//Computer Vi sion and Pattern Recognition. Xi' an, China: IEEE, 2010 : 231-238.
  • 5Daniel G,Shai B, Michal I. Super resolution from a single image[C]//International Conference on Computer Vi- sion. Kyoto ,Japan: IEEE, 2009 : 349-356.
  • 6Su H, Tang L, Wu Y. Spatially adaptive block based su- per resolution[J]. IEEE Transactions on Image Process- ing,2012,21(3) :1031-1045.
  • 7张新明,沈兰荪.基于多尺度边缘保持正则化的超分辨率复原[J].软件学报,2003,14(6):1075-1081. 被引量:29
  • 8Dai Shengyang, Han Mei, Xu Wei, et al. SoftCuts: a soft edge smoothness prior for color image super-resolution [J]. IEEE Transactions on Image Processing, 2009, 18 (5) :969-981.
  • 9Yuri B, Vladimir K. Computing geodesics and minimal s urfaces via graph cuts[C]//International Conference on Computer Vision. Nice, France : IEEE, 2003 :26-33.

二级参考文献19

  • 1Ur H, Gross D. Improved resolution from sub-pixel shifted pictures. CVGIP: Graph. Models Image Processing, 1992,54(2): 181-186.
  • 2Kim S, Su WY. Recursive high-resolution reconstruction of blurred multi-frame images. IEEE Transactions on Image Processing,1993,2(4):534-539.
  • 3Shah NR, Zakhor A. Resolution enhancement of color video sequences. IEEE Transactions on Image Processing, 1999,8(6):879-885.
  • 4Irani M, Peleg S. Improving resolution by image registration. CVGIP: Graph. Models Image Process, 1991,53(3):231-239.
  • 5Patti A J, Sezan MI, Tekalp AM. Super-Resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time.IEEE Transactions on Image Processing, 1997,6(8):1064-1076.
  • 6Eren PE, Sezan MI, Tekalp AM. Robust, object-based high-resolution image reconstruction from low-resolution video. IEEE Transactions on Image Processing, 1997,6(8): 1446-1451.
  • 7Schultz RR, Stevenson RL. Extraction of high-resolution frames from video sequences. IEEE Transactions on Image Processing,1996,5(6);996-1011.
  • 8Hardie RC, Barnard KJ, Armstrong EE. Joint MAP registration and high-resolution image estimation using a sequence of undersampled images. IEEE Transactions on Image Processing, 1997,6(12): 1621 - 1633.
  • 9Baker S, Kanade T. Limits on super-resolution and how to break them. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002,24(9): 1167- 1183.
  • 10Nguyen N, Milanfar P, Golub G. A computationally efficient super-resolution image reconstruction algorithm. IEEE Transactions on Image Processing, 2001,10(4):573-583.

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