系统仿真学报 ›› 2016, Vol. 28 ›› Issue (9): 2169-2175.

• 短文 • 上一篇    下一篇

一种基于梯度与视觉显著度的图像缩放方法

蔡兴泉1, 布尼泓灏1, 乔雨晴1,2, 柳静华1,3, 李凤霞4   

  1. 1.北方工业大学计算机学院, 北京 100144;
    2.肯尼索州立大学新媒体系, 美国 亚特兰大 30060;
    3.兴唐通信科技有限公司, 北京 100191;
    4.北京理工大学智能信息技术北京市重点实验室, 北京 100081
  • 收稿日期:2016-05-30 修回日期:2016-07-14 出版日期:2016-09-08 发布日期:2020-08-14
  • 作者简介:蔡兴泉(1980-),男,山东,博士,副教授,研究方向为虚拟现实。
  • 基金资助:
    国家自然科学基金(61503005),北京市自然科学基金(4162022),北方工业大学长城学者(CC08)

Image Resizing Method Based on Gradient and Visual Saliency

Cai Xingquan1, Buni Honghao1, Qiao Yuqing1,2, Liu Jinghua1,3, Li Fengxia4   

  1. 1. School of Computer Science, North China University of Technology, Beijing 100144, China;
    2. Department of New Media, Kennesaw State University, Atlanta 30060, USA;
    3. Xingtang Communications Technology Co. Ltd, Beijing 100191, China;
    4. Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing 100081, China
  • Received:2016-05-30 Revised:2016-07-14 Online:2016-09-08 Published:2020-08-14

摘要: 提出了一种面向移动应用的基于梯度与视觉显著度的图像缩放方法。对原图像灰度化后,考虑邻域像素的梯度影响,计算图像梯度能量矩阵;建立视觉显著度模型,将视觉显著度能量矩阵与图像梯度能量矩阵加权相加,得到复合能量矩阵;根据复合能量矩阵,计算图像的累计最小能量矩阵和能量最小轨迹矩阵,计算图像的最小能量缝合线;采用水平垂直穿插顺序,对缝合线进行删除或插入实现图像缩放。结果表明,梯度能量与视觉显著度能量加权的复合能量图像能更好的识别图像目标区域;进行缩放时,丢弃了特征不明显的背景,保留了目标图像特征,明显优于传统方法。

关键词: 图像缩放, 视觉显著度, 梯度能量, 最小能量缝合线

Abstract: In order to delete the image region without obvious features, and not damage the main features of the target for mobile applications, the image resizing method was provided based on gradient and visual saliency. The original image was grayed, and the gradient energy matrix from the gradient of neighborhood pixels was obtained. The complex energy matrix was obtained by weighted sum of visual saliency energy and image gradient energy matrix. The cumulative energy matrix and minimal energy trajectory matrix were calculated, and the minimal energy seam of image was got. The image resizing was completed by deleting the minimal energy seam in horizontal vertical interspersed sequence. The experiments results show that the complex energy matrix combined the gradient energy with visual saliency energy can recognize target object better, and this method discards the background without obvious features and preserves target object features.

Key words: image resizing, visual saliency, gradient energy, minimal energy seam

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