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Visual Saliency Based on Two-Dimensional Fractional Fourier Transform

  • Haibo Xu
  • Chengshun JiangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1120)

Abstract

Visual saliency is very helpful for image detection and image processing. This paper proposes a novel visual saliency model. First, the proposed model can extract a saliency map with high precision and compound the linear combination of saliency map. Second, based on two-dimensional fractional Fourier transform, the proposed model generates a robust saliency map from the input image with Gaussian or salt-and-pepper noise. In order to reveal the noise influence from the given image, we provide a concept called the noise sensitivity scale (NSS). Third, using the image database from MSRA10K, we analyze the precision-recall and ROC curve and experimentally demonstrate that the proposed model can evaluate human fixation to some extent.

Keywords

Image processing Computer vision Fractional Fourier transform 

Notes

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this article.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Robot EngineeringYangtze Normal UniversityChongqingPeople’s Republic of China
  2. 2.College of Big Data and Intelligent EngineeringYangtze Normal UniversityChongqingPeople’s Republic of China

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