Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability.

中文翻译：

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基于视觉仿生的多通道显着性检测

受人眼视觉特性的启发，将视觉注意力的深度信息融入到显着性检测中，有效解决相似或复杂背景干扰下精度低、稳定性差等问题。首先，采用改进的SLIC算法对RGBD图像进行分割和聚类。其次，根据各向异性中心-环绕差分法获得图像区域的深度显着性。然后根据人类视觉的颜色感知规律计算RGB图像的全局特征显着性。将得到的多通道显着图基于信息熵进行加权融合，突出目标区域，得到最终的检测结果。该方法的工作复杂度为O(N)，实验结果表明，基于视觉仿生的算法有效抑制了相似或复杂背景的干扰，具有较高的准确度和稳定性。