Saliency Detection Using Wavelet Transform in Hypercomplex Domain

Ying YU; Qinglong WU; Kaixuan SHAO; Yuxing KANG; Jian YANG

doi:10.11999/JEIT180738

Volume 41 Issue 9

Sep. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(9): 2231-2238

Ying YU, Qinglong WU, Kaixuan SHAO, Yuxing KANG, Jian YANG. Saliency Detection Using Wavelet Transform in Hypercomplex Domain[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2231-2238. doi: 10.11999/JEIT180738

Citation:

Ying YU, Qinglong WU, Kaixuan SHAO, Yuxing KANG, Jian YANG. Saliency Detection Using Wavelet Transform in Hypercomplex Domain[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2231-2238. doi: 10.11999/JEIT180738

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Saliency Detection Using Wavelet Transform in Hypercomplex Domain

doi: 10.11999/JEIT180738

School of Information Science and Engineering, Yunnan University, Kunming 650500, China

Funds: The National Natural Science Foundation of China (61263048), Yunnan Province Applied Basic Research Project (2018FB102), The “Young and Middle-Aged Backbone Teachers” Cultivation Plan of Yunnan University (XT412003)

Received Date: 2018-07-20
Rev Recd Date: 2019-02-17

Available Online: 2019-03-16

Publish Date: 2019-09-10

Abstract

Abstract

To solve the incompleteness of the salient region obtained by the existing saliency detection method in the frequency domain, a frequency saliency detection method of multi-scale analysis is proposed. Firstly, the quaternion hypercomplex is constructed by the input image feature channels. Then, the multi-scale decomposition of the quaternion amplitude spectrum is performed by wavelet transform, and the multi-scale visual saliency map is calculated. Finally, the better saliency map is fused based on the evaluation function, and central bias is used to generate the final visual saliency map. The experimental results show that the proposed method can effectively suppress the background interference, find significant target quickly and accurately, and have high detection accuracy.
- Image processing,
- Saliency detection,
- Saliency map,
- Visual attention,
- Hypercomplex Fourier transform,
- Wavelet transform

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References(23)

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