Image Retargeting with Seam-Carving Combining Saliency and Depth Information

WU Jia-ying; YANG Sai; DU Jun; DONG Ning

doi:10.3969/j.issn.0372-2112.2019.07.020

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Image Retargeting with Seam-Carving Combining Saliency and Depth Information

更新时间：2025-07-16

- Image Retargeting with Seam-Carving Combining Saliency and Depth Information
- Acta Electronica Sinica Vol. 47, Issue 7, Pages: 1547-1550(2019)
- 作者机构：
  
  1. 南通大学电气工程学院,江苏,南通,226019
  2. 南通先进通信技术研究院,江苏,南通,226019
  3. 南通大学电气工程学院,江苏,南通,226019
  4. 南通先进通信技术研究院,江苏,南通,226019
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2019.07.020
  CLC： TP391
- Published Online：25 July 2019，
  
  Published：2019
- 稿件说明：
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WU Jia-ying, YANG Sai, DU Jun, et al. Image Retargeting with Seam-Carving Combining Saliency and Depth Information[J]. Acta Electronica Sinica, 2019, 47(7): 1547-1550.
DOI：

WU Jia-ying, YANG Sai, DU Jun, et al. Image Retargeting with Seam-Carving Combining Saliency and Depth Information[J]. Acta Electronica Sinica, 2019, 47(7): 1547-1550. DOI： 10.3969/j.issn.0372-2112.2019.07.020.

摘要

针对当前内容感知的重定向方法中可能出现的变形和失真问题，提出一种融合显著与深度信息的缝切割重定向方法.首先利用GBVS算法获取图像显著信息，结合图像梯度信息与通过SIFT匹配方法获取的图像深度信息构建更精确的重要度图；其次，根据重要度图的能量分布，对原始图像进行处理，得到最终的重定向结果.基于公开数据库在两个不同评价标准下与多种重定向方法的对比表明，本文方法能够最大程度的保留图像的显著部分.

Abstract

To solve the problem of deformation and distortion that may occur in the current content-aware redirection method

a retargeting method with seam-carving combining saliency and depth information is proposed. Specifically

the GBVS algorithm is used to obtain the saliency information

and the image gradient information is combined with the image depth information acquired by the SIFT matching method to construct a more accurate importance map. Then

according to the energy distribution of the importance map

the original image is processed to obtain the final results. The comparison on the public database with different methods under two evaluation criteria shows that the proposed method can preserve the significant part of the image to the greatest extent.

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