Share Email Print

Journal of Electronic Imaging

Spectral saliency via automatic adaptive amplitude spectrum analysis
Author(s): Xiaodong Wang; Jialun Dai; Yafei Zhu; Haiyong Zheng; Xiaoyan Qiao
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Suppressing nonsalient patterns by smoothing the amplitude spectrum at an appropriate scale has been shown to effectively detect the visual saliency in the frequency domain. Different filter scales are required for different types of salient objects. We observe that the optimal scale for smoothing amplitude spectrum shares a specific relation with the size of the salient region. Based on this observation and the bottom-up saliency detection characterized by spectrum scale-space analysis for natural images, we propose to detect visual saliency, especially with salient objects of different sizes and locations via automatic adaptive amplitude spectrum analysis. We not only provide a new criterion for automatic optimal scale selection but also reserve the saliency maps corresponding to different salient objects with meaningful saliency information by adaptive weighted combination. The performance of quantitative and qualitative comparisons is evaluated by three different kinds of metrics on the four most widely used datasets and one up-to-date large-scale dataset. The experimental results validate that our method outperforms the existing state-of-the-art saliency models for predicting human eye fixations in terms of accuracy and robustness.

Paper Details

Date Published: 12 April 2016
PDF: 15 pages
J. Electron. Imag. 25(2) 023020 doi: 10.1117/1.JEI.25.2.023020
Published in: Journal of Electronic Imaging Volume 25, Issue 2
Show Author Affiliations
Xiaodong Wang, Ocean Univ. of China (China)
Jialun Dai, Ocean Univ. of China (China)
Yafei Zhu, Ocean Univ. of China (China)
Haiyong Zheng, Ocean Univ. of China (China)
Xiaoyan Qiao, Shandong Institute of Business and Technology (China)

© SPIE. Terms of Use
Back to Top