计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 192-198.doi: 10.11896/jsjkx.191000101

• 计算机图形学&多媒体 • 上一篇    下一篇

一种基于显式SURF特征保留的图像重定向算法

赵亮, 彭宏京, 杜振龙   

  1. 南京工业大学计算机科学与技术学院 南京 211816
  • 收稿日期:2019-10-16 修回日期:2020-03-17 出版日期:2020-11-15 发布日期:2020-11-05
  • 通讯作者: 彭宏京(penghongjing@163.com)
  • 作者简介:2378935325@qq.com
  • 基金资助:
    国家自然科学基金项目(61672279)

Content-aware Image Retargeting Algorithm Based on Explicit SURF Feature Preservation

ZHAO Liang, PENG Hong-jing, DU Zhen-long   

  1. School of Computer Science and Technology,Nanjing University of Technology,Nanjing 211816,China
  • Received:2019-10-16 Revised:2020-03-17 Online:2020-11-15 Published:2020-11-05
  • About author:ZHAO Liang,born in 1994,postgra-duate.His main research interests include image processing and computer vision.
    PENG Hong-jing,born in 1965,Ph.D,associate professor,is a member of China Computer Federation.His research interests include pattern recognition and computer vision,data mining and machine learning.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61672279).

摘要: 图像重定向是一种通过调整图像大小,使其适合于任意显示终端高宽比的数字媒体处理技术。现有的图像重定向研究大多集中在重要对象的形状保持上,而对人类视觉系统敏感的图像关键特征缺乏充分考虑,导致视觉接受度较低。由此,提出了一种新的基于显式的SURF特征保留的图像重定向算法。不同于一般的基于顶点或轴对齐的网格编码形式的网格变形技术,该方法采用基于网格边的网格变形技术。首先定义一个仿射矩阵,使得每条网格边根据仿射矩阵进行变形,从而形成一个基本的基于网格边的变形模型;然后通过SURF特征检测得到SURF特征区域,再将网格边范围约束至SURF特征区域,以此达到特征保留的效果;最后得到一个新的网格变形模型。另外,通过在基本网格变形模型的基础上设置一个稀疏能量项,即给每条网格边赋初始权重以使网格线彼此稀疏,来解决网格线自交的问题;而且在必要时在迭代求解的过程中还可更新此权重。通过实验将所提方法与两种现有的图像重定向方法进行图像质量评估,结果表明所提方法能够在图像重定向过程中最小化失真,同时产生较好的视觉效果,得分增益最高可分别达到16.0%和9.7%。

关键词: SURF特征保留, 二维网格变形, 内容感知图像重定向, 图像翘曲方法, 图像质量评估

Abstract: Image retargeting is a digital media processing technique that adjusts the image size to fit the target resolution of any display device aspect ratio.Most of the existing research on image retargeting focuses on the shape preservation of important objects,while the key features of images are sensitive to the human visual system are not fully considered,resulting in lower visual acceptance.Therefore,a new image retargeting algorithm based on explicit SURF feature preservation is proposed.Different from the general mesh deformation technology based on vertex or axis alignment,the mesh deformation technique based on mesh edge is adopted.First,an affine matrix is defined,so that each mesh edge is deformed according to the affine matrix to form a basic mesh edge-based deformation model.Then,the SURF feature region is obtained by SURF feature detection,and the mesh edge range is constrained to the SURF feature region to achieve the feature preservation effect.Thereby,a new mesh deformation mo-del is obtained.In addition,a sparse energy term is set on the basis of the basic mesh deformation model,that is,assigning initial weights to each mesh edge to make the grid lines sparse each other,thereby solving the problem of grid line self-intersection.This weight can also be updated during the iterative solution process if necessary.Finally,an image quality assessment is performed between the proposed method and two existing image retargeting methods.The proposed method can minimize the distortion and produce better visual effects during the image retargeting process.The highest score gain can reach 16.0% and 9.7%,respectively.

Key words: 2D mesh deformation, Content-aware image retargeting, Image quality assessment, Image warping method, SURF feature preservation

中图分类号: 

  • TP391
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