An Image Saliency Detection Method Based on Combining Global and Local Information

被引:0
|
作者
Yang, Hangxu [1 ,2 ]
Gong, Yongjian [1 ]
Wang, Kai [3 ]
机构
[1] Jinhua Polytech, Coll Mech & Elect Engn, Jinhua 321017, Zhejiang, Peoples R China
[2] Key Lab Crop Harvesting Equipment Technol Zhejian, Jinhua 321017, Zhejiang, Peoples R China
[3] Nanjing Agr Univ, Coll Engn, Nanjing 210031, Jiangsu, Peoples R China
关键词
Compendex;
D O I
10.1155/2022/1849995
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the field of computer vision, image saliency target detection can not only improve the accuracy of image detection but also accelerate the speed of image detection. In order to solve the existing problems of the saliency target detection algorithms at present, such as inconspicuous texture details and incomplete edge contour display, this paper proposes a saliency target detection algorithm integrating multiple information. The algorithm consists of three processes: preprocessing process, multi-information extraction process, and fusion optimization process. The frequency domain features of the image are calculated, the algorithm calculates the frequency domain features of the image, introduces power law transform and feature normalization, improves the frequency domain features of the image, saves the information of the target region, and inhibits the information of the background region. On three public MSRA, SED2, and ECSSD image datasets, the proposed algorithm is compared with other classical algorithms in subjective and objective comparison experiments. Experimental results show that the proposed algorithm can not only accurately and comprehensively extract significant target regions but also retain more texture information and complete edge information while satisfying the human visual experience. All evaluation indexes are significantly better than the comparison algorithm, showing good reliability and adaptability.
引用
收藏
页数:13
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