基于SIFT和加权信息熵的红外小目标检测

Detecting Infrared Small Targets Based on SIFT and Weighted Entropy

针对红外图像中弱小目标的检测需求,文中提出基于尺度不变特征变换Scale Invariant Feature Transform(SIFT)和加权信息熵的红外小目标检测算法。该方法根据红外小目标的成像特点,采用SIFT特征描述子进行关键点的提取,利用帧间的匹配初步获得了目标的可能位置;进一步使用红外图像加权信息熵得到图像在灰度信息和平均信息量意义下的特征;再针对复杂云背景成像弱小目标实时检测的需要对计算出的特征进行再一次判定进而检测出目标。实验结果表明该方法在天空云背景中处理效果较好,具有良好鲁棒性。

To satisfy the requirement of detecting small targets in infrared image,an infrared targets detecting arithmetic is put forward based on Scale Invariant Feature Transform（SIFT） and weighted entropy.The method considered the imaging character of small targets.SIFT feature is used to extract special points and the possible location of target is obtained through the match between frames.Weighted information entropy is applied to find feature of gray scale information and entropy.Then potential targets are judged again by the features which have been calculated for the need of real-time dim small targets detection in heavy cloud clutter and complex infrared backgrounds.Experiment indicates that the method has an advanced practicability,and the performance of robustness is good in the sky background.