人类视觉注意机制在目标检测中的应用

根据人类视觉感知理论，在介绍了两种比较有代表性的视觉注意模型的基础上，采用bottom—up控制策略的预注意机制和top—down控制策略的注意机制，提出了一种适用于自动目标识别的目标检测算法。从输入图像出发，采用Gabor算子建立多尺度、多方位的多通道图像，通过全波整流和各通道间的对比度增益控制，得到多尺度、多方位的方位特征图，这些特征图的线性组合则为显著性图。给出了仅采用bottom—up控制策略的船舶目标检测实验结果，待检测目标在显著性图中得到明显增强，有利于检测的实现。

Applications of human visual attention mechanisms in object detection

Two models of visual attention which are consistent with human visual perception are introduced. Based on these two models, an ATR algorithm employing attention mechanisms with bottom-up and top-down control strategies is developed. A multi-channel representation of the input image was obtained by a bank of Gabor filters, corresponding to multiple scales and multiple orientations. Full-wave rectification of each channel and contrast gain control among the channels were performed sequentially to get orientation feature maps with multiple scales and multiple orientations. The so-called salient map was the linear combination of these orientation feature maps. The experimental result with ship detection is given by use of bottom-up control strategy only. The objects for detection are effectively enhanced on the result map.