介绍了一种新的微小型楔环形贫点阵红外探测器, 着重研究了其特殊的探测机制。采用合并像素的方式仿真生成楔环形贫点阵图像, 借助对数极坐标变换分析得出, 它在中心处信息量大, 在边缘处信息量小。以灰度直方图作为统计手段和依据, 采用自适应类直方图实时阈值分割的方法, 完成目标的检测; 采用基于状态机循环处理的目标跟踪方法, 对目标可能所处的状态进行划分, 并利用序列图像估计位置和速度信息, 完成目标的跟踪。应用基本图元对楔环形贫点阵图像进行测试, 对于不同形状不同朝向的基本图元, 结合像元灰度值之间的比例关系, 能够将其区分。结果表明, 楔环形贫点阵探测器用于目标探测与识别的可能性是存在的, 继续相关研究很有意义。

A new micro wedge-ring poor pixels infrared detector is presented, and its special detecting principles are expatiated. The simulated wedge-ring poor pixels images are formed by merging picture elements. Further, with the help of log-polar transformation, it can be easily found that there is much information in the center and little on the edge. Based on grey histogram, targets are detected by using an adaptive real-time threshold segmentation algorithm, and are tracked by adopting a tracking algorithm. In the tracking algorithm the possible states of target were partitioned, and the target position and velocity were estimated on the basis of sequence images. Utilizing the basic geometric figures the wedge-ring poor pixels images are tested. For the different shape basic figures with different orientations, their externalities are mostly different. Even though some have similarities, they can be distinguished by the proportion of pixels’ grey values. The results show that the possible application of poor pixels detector in the target detection and recognition system and it is very significant to continue corresponding research.