Qi Shengxiang, Ming Delie, Ma Jie, Sun Xiao, Tian Jinwen
Appl Opt. 2014 Jun 20;53(18):3929-40. doi: 10.1364/AO.53.003929.
In this paper, we present an infrared small target detection method based on Boolean map visual theory. The scheme is inspired by the phenomenon that small targets can often attract human attention due to two characteristics: brightness and Gaussian-like shape in the local context area. Motivated by this observation, we perform the task under a visual attention framework with Boolean map theory, which reveals that an observer's visual awareness corresponds to one Boolean map via a selected feature at any given instant. Formally, the infrared image is separated into two feature channels, including a color channel with the original gray intensity map and an orientation channel with the orientation texture maps produced by a designed second order directional derivative filter. For each feature map, Boolean maps delineating targets are computed from hierarchical segmentations. Small targets are then extracted from the target enhanced map, which is obtained by fusing the weighted Boolean maps of the two channels. In experiments, a set of real infrared images covering typical backgrounds with sky, sea, and ground clutters are tested to verify the effectiveness of our method. The results demonstrate that it outperforms the state-of-the-art methods with good performance.
在本文中，我们提出了一种基于布尔地图视觉理论的红外小目标检测方法。该方案的灵感来源于小目标由于两个特征（在局部上下文区域中的亮度和类高斯形状）常常能够吸引人类注意力这一现象。受此观察启发，我们在视觉注意力框架下利用布尔地图理论执行该任务，该理论表明观察者的视觉感知在任何给定时刻通过所选特征对应于一个布尔地图。形式上，红外图像被分离为两个特征通道，包括一个具有原始灰度强度图的颜色通道和一个具有由设计的二阶方向导数滤波器生成的方向纹理图的方向通道。对于每个特征图，从分层分割中计算出描绘目标的布尔地图。然后从小目标增强图中提取小目标，小目标增强图是通过融合两个通道的加权布尔地图获得的。在实验中，测试了一组覆盖具有天空、海洋和地面杂波等典型背景的真实红外图像，以验证我们方法的有效性。结果表明，该方法性能优于当前最先进的方法。
