提出了一种基于分块图像统计特征的红外目标提取方法,首先将图像逐步分成越来越小的块,根据块图像统计特征构造函数求其极大值,获得目标的种子区域和包含整个目标的约束区域;然后在约束区域内,将一种快速的区域生长方法用于目标种子区域的生长,最终提取出红外目标.通过对不同目标大小的红外飞机图像的实验,验证了算法的有效性.对算法在TI公司的DSP芯片TMS320VC33-150上实现的时间消耗进行了估算,结果表明可以达到实时提取目标的要求.

Based on statistical feature of image blocks, a method for infrared object extraction is proposed. Firstly, the entire image is divided into blocks with scale decreasing gradually. According to the maximal value of the functions composed of statistical feature, seed region of the object and confined region that contains the entire object are obtained. Within the confined region, a fast method of region growing is applied to the seed region, and infrared object is extracted finally. Infrared aircraft images of varying object size are experimented to demonstrate the effectiveness of the proposed algorithm. Consuming time is also estimated if the proposed algorithm is implemented on the digital signal processor TMS320VC33-150, and it meets the requirement for real-time object extraction