[1]李霞,李富生,陈园琴.基于视觉灵敏度与DCT系数的显著性检测[J].深圳大学学报理工版,2014,31(5):464-472.[doi:10.3724/SP.J.1249.2014.05464]
 Li Xia,Li Fusheng,and Chen Yuanqin.Saliency detection model based on human visual sensitivity and DCT coefficients[J].Journal of Shenzhen University Science and Engineering,2014,31(5):464-472.[doi:10.3724/SP.J.1249.2014.05464]
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基于视觉灵敏度与DCT系数的显著性检测()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第31卷
期数:
2014年第5期
页码:
464-472
栏目:
电子与信息科学
出版日期:
2014-09-20

文章信息/Info

Title:
Saliency detection model based on human visual sensitivity and DCT coefficients
文章编号:
201405004
作者:
李霞1李富生1陈园琴2
1)深圳大学信息工程学院,深圳市现代通信与信息处理重点实验室,深圳 518060;
2)南昌大学电子工程学院,南昌330031
Author(s):
Li Xia1 Li Fusheng1 and Chen Yuanqin2
1) College of Information Engineering, Shenzhen University, Shenzhen Key Laboratory of ACIP, Shenzhen 518060, P.R.China
2) Information Engineering Schoot, Nanchang University, Nanchang 330031, P.R.China
关键词:
图像处理 显著性检测 离散余弦变换 空间距离 人类视觉灵敏度 眼动跟踪数据 视频编码
Keywords:
image processing saliency detect discrete cosine transformation spatial distance human visual sensitivity eye-tracking dataset video coding
分类号:
TP 391
DOI:
10.3724/SP.J.1249.2014.05464
文献标志码:
A
摘要:
提出一种基于人类视觉灵敏度与空间加权离散余弦系数差异度的显著性检测模型.该模型将图像块的离散余弦低频系数作为其特征向量,以取代颜色和亮度等基本特征.每个图像块的显著性不仅计算与其余所有图像块的空间加权特征差异度之和,还用人类视觉灵敏度加权.通过与6种典型的显著性检测模型在3个眼动跟踪数据集上进行对比实验,结果表明,该模型显著性检测性能优于所有对比算法.此外,将该显著性检测模型用于新一代高效率视频编码(high efficiency video coding,HEVC)中也获得了很好的效果.
Abstract:
A new saliency detection model based on human visual sensitivity and spatial weighted dissimilarity of discrete cosine transformation (DCT) coefficients is proposed. The DCT coefficients were used as the feature vector to replace the color and intensity of image patches to compute contrast. The salient value for each image patch was calculated not only by the dissimilarity between the DCT coefficients of this patch and other patches in the whole image but also by the dissimilarity in weighted human visual sensitivity. The experimental results show that the proposed saliency detection model outperforms other state-of-the-art detection models in three eye-tracking datasets. In addition, the proposed model is also applied to new video coding technology, namely high efficiency video coding (HEVC), and achiev better performance than conventional algorithms.

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备注/Memo

备注/Memo:
Received:2014-05-09;Accepted:2014-07-09
Foundation:Science and Technology Planning Project of Guangdong Province(2011B010200045);Accelerated Programs of Shenzhen Key Laboratory(CXB201105060068A)
Corresponding author:Professor Li Xia.E-mail: lixia@szu.edu.cn
Citation:Li Xia,Li Fusheng,Chen Yuanqin.Saliency detection model based on human visual sensitivity and DCT coefficients[J]. Journal of Shenzhen University Science and Engineering, 2014, 31(5): 464-472.(in Chinese)
基金项目:广东省科技计划资助项目(2011B010200045);深圳市重点实验室提升项目(CXB201105060068A)
作者简介:李霞(1968—),女(汉族),四川省乐山市人,深圳大学教授、博士生导师.E-mail:lixia@szu.edu.cn
引文:李霞,李富生,陈园琴.基于视觉灵敏度与DCT系数的显著性检测[J]. 深圳大学学报理工版,2014,31(5):464-472.
更新日期/Last Update: 2014-09-11