计算机科学 ›› 2014, Vol. 41 ›› Issue (8): 47-49.doi: 10.11896/j.issn.1002-137X.2014.08.009

• 2013年全国理论计算机科学学术年会 • 上一篇    下一篇

基于非局部POCS的超分辨率图像重建

罗国中,殷建平,祝恩   

  1. 国防科技大学计算机学院 长沙410073;国防科技大学计算机学院 长沙410073;国防科技大学计算机学院 长沙410073
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金资助

Super-resolution Image Reconstruction Based on Non-local POCS

LUO Guo-zhong,YIN Jian-ping and ZHU En   

  • Online:2018-11-14 Published:2018-11-14

摘要: 图像获取过程中,受成像系统的影响,无法获取原始场景中所有的信息。超分辨率图像重建技术就是在不改变成像系统的前提下,提高图像质量。POCS(凸集投影算法)可以利用多帧低分辨率图像重建一帧高分辨率图像。然而传统的POCS算法通常会产生“锯齿”边缘。在自然图像中,会存在许多的相似边缘结构。利用局部相似性的结构,可以有效地消除“锯齿”边缘。因此提出一种基于非局部POCS的超分辨率图像重建算法,以有效锐化图像边缘,提高图像的视觉感观。

关键词: 超分辨率重建,POCS(凸集投影),非局部均值滤波,图像插值

Abstract: Image acquisition process,affected by the imaging system,cannot get all the information of the original scene.Super-resolution image reconstruction is the technique to boost image quality under the premise of not changing the imaging system.POCS (projection onto convex sets algorithm) can take advantage of multi-frame low-resolution ima-ge to reconstruct a high resolution image.However,the traditional POCS algorithm usually produces the “jaggy” edge.In nature images,there will be many similar-edge structure.Taking advantage of local similarity structure can effectively eliminate the “jaggy” edge.Therefor a non-local POCS-based super-resolution image reconstruction algorithm was proposed.It can sharpen image edge effectively,and improve the visual senses of the image.

Key words: Super-resolution reconstruction,POCS (convex set projection),Non-local mean filtering,Image interpolation

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