Saliency Detection Using Wavelet Transform in Hypercomplex Domain
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摘要: 针对现有频域显著性检测方法得到的显著区域不完整的问题，该文提出一种多尺度分析的频率域显著性检测方法。首先由输入图像特征通道信息构建4元超复数，然后通过小波变换对4元超复数域中幅度谱进行多尺度分解，计算生成多尺度下的视觉显著图，最后由评价函数选出效果较好显著图合成最终视觉显著图。实验结果表明，该文方法能够有效地抑制背景干扰，快速、精确地找到完整的显著目标，具有较高的检测精确度。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.
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表 1 注视点AUC得分
注视点 本文算法 HFT PQFT SR IT SUN MSS HC 全部 0.8328 0.8046 0.7570 0.6228 0.5365 0.6729 0.6558 0.5766 2个 0.8831 0.8402 0.7696 0.6274 0.5444 0.6746 0.6698 0.5853 
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表 3 算法计算速度(s)
方法 本文算法 HFT PQFT SR IT SUN MSS HC 时间 0.0832 0.0936 0.0198 0.0081 0.2697 1.6185 0.0767 0.6585
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