一种基于视觉注意的小目标检测方法

为了方便而快速地在图像中标出目标，提出了一种基于视觉注意的小目标检测方法。该方法对Itti通用视觉注意计算模型作了改进，将目标检测过程分为亮目标检测和暗目标检测。其中亮目标检测采用了简化的Itti模型，暗目标检测主要采用侧抑制网络模型，将亮目标检测与暗目标检测各自生成的显著图合成得到最终的显著图。通过设定一阈值得到图像的预注意区域，采用模糊C-均值算法进行图像分割，以便相对完整地标出每个目标。结果表明，算法能够有效地检测待检测目标。

Small target detection method based on visual attention

A small target detection method based on visual attention is presented aiming at easily and quickly marking the targets in the image. In this method, Itti’s common visual attention computational model has been improved and the target detection process is divided into bright target detection and dark target detection. In bright target detection, a simplified Itti’s model is put to use, and in dark target detection, this paper mainly builds a lateral inhibition network model. It can synthetize the two saliency maps formed in bright target detection and dark target detection to get the final saliency map. After that a threshold is set to get the pre-attention region in the image. In order to mark each target relatively integral, fuzzy C-means algorithm is used for image segmentation. It shows that the proposed algorithm can detect the targets to be detected effectively.