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Kyushu Institute of Technology
Kyushu Institute of Technology
Kyushu Institute of Technology
Japan University of Economics
Kyushu Institute of Technology
抄録
In this paper, we present a novel approach to saliency detection. We define a visually salient region in an image with following two properties; global spatial redundancy, i.e., mutual-information, and local saliency, i.e., self-information or simply the region complexity. The former is its probability of occurrence within the image, whereas the latter defines how much information is contained within a region, and it is quantified by the entropy. By combining the global spatial redundancy measure and local entropy, we can achieve a simple, yet robust saliency detector. We evaluate it quantitatively and qualitatively. The comparison to Itti et al. [6], the spectral residual approach by Hou and Zhang [5], Achanta et al. [13] as well as to Zhai and Shah [14], on publicly available data shows a significant improvement.
雑誌名
Biomedical Soft Computing and Human Science
巻
19
号
1
ページ
69 - 73
発行年
2014-04
出版者
バイオメディカル・ファジィ・システム学会
書誌レコードID
AA11509989
権利
Copyright (c) Biomedical Fuzzy Systems Association
A Saliency Detection Technique Considering Self- and Mutual-Information
e2014-19-1-sl01.pdf
(374.13KB)
