利用红外夜视的海上弱小目标检测与分割

Detection and segmentation of micro sea target by use of infrared night vision

红外夜视检测技术能加强海上预警探测系统的安全性,但红外夜视仪所采集的海上红外图像存在大量“背景杂波”,严重干扰弱小目标的准确检测。针对此问题,结合主动轮廓模型与插值滤波器提出一种用于海上安全系统的红外夜视弱小目标检测算法。该算法先分别采用全局主动轮廓与局部主动轮廓搜索感兴趣目标区域,通过双层主动轮廓模型消除噪声与背景杂波对目标检测的影响。然后提出变化方向的插值滤波器沿着感兴趣区域的边缘进行滤波,缓解弱边缘对目标真实边缘的干扰。在真实的红外夜视海上图像集上对该算法进行了实验与分析,结果表明该算法能改善海上弱小目标的检测性能,对提高海上航行的安全性具有积极意义。

Infrared night vision technique is effective on the security enhancement of sea early warning detection system, but the sea images captured by the infrared night vision viewer usually contain an amount of “background clutter”, it leads to obvious detection performance reduction of sea micro targets. To solve this problem, both active contour model and interpolation filter are combined to propose an accuracy micro target detection algorithm of infrared night vision. Firstly, this algorithm uses global active contour model and local active contour model to search the region of interest, respectively, thus by use of double-layer active contour models, the bad impact of noise and clutter on target detection are eliminated. Then, the interpolation filter with direction variation is proposed to filter the region of interest along the edge, in order to reduce the interference of week edges with the target real edge. Experiments and analysis are carried on the real infrared night vision sea image set, the results show that the proposed method can improve the detection performance of sea micro targets, this algorithm is good for sail on the sea.