基于对数Gabor的超复数视觉显著性检测算法

Hypercomplex Visual Saliency Detection Algorithm Based on Log-Gabor

为在没有先验知识的情况下准确获取图像显著性目标,提出一种基于对数Gabor滤波器和超复数傅里叶变换的视觉显著性检测算法。利用对数Gabor滤波器模仿人类视觉感受野,对输入图像进行预处理,提取颜色、纹理方向等特征。根据所得特征构造各尺度下的超复数图像,并求其傅里叶变换相位谱,将多尺度超复数相位谱反变换后进行归一化,从而获得视觉显著图。实验结果表明,该算法与传统的算法相比具有更高的准确率,应用于复杂场景下的交通标志检测能取得较好的检测效果。

In order to obtain more accurate salient object from an image in the absence of priori knowledge,this paper proposes a visual saliency detection algorithm based on Log-Gabor filter and hypercomplex Fourier transform.It uses Log-Gabor filter to process input image and obtain color and texture feature,constructs a hypercomplex image using feature images,and calculates its Fourier transform phase spectral.It calculates visual saliency map by normalization.Experimental results show that the proposed method outperforms state-of-the-art methods remarkably in visual saliency and has better detection results in traffic sign detection.