基于小波变换与灰度形态学滤波的双波段红外图像弱目标融合检测

Detection of Dual Band IR Small Target Fusion Detection based on Wavelet Transformation and Grayscale Morphology Filtering

针对舰载红外搜索与跟踪系统中的弱目标检测问题,本文首先提出了一种采用小波变换与灰度形态学滤波相结合的背景抑制与目标增强算法;然后基于所提出的背景抑制与目标增强算法设计了一种双波段红外图像弱目标融合检测方法;最后采用实际的双波段红外图像序列对所提出的背景抑制与目标增强算法和所设计的双波段红外图像弱目标融合检测方法进行了实验测试,并给出了详细的分析与比较。实验结果显示所提出的背景抑制与目标增强算法在较大程度上改善了在信噪比条件下的红外图像弱目标检测效率,而双波段红外图像的应用进一步提高了系统的目标检测性能。

Aim at the problem of small target detection for the Infrared Search and Track systems, this paper firstly proposed a algorithm for hackground suppression and target enhancing that integrated wavelet transformation and grayscale morphology filtering; Then developed a method of dual band IR weak target fusion detection based the proposed algorithm. Finally analyzed and compared the proposed background suppression and target enhancing algorithm and the developed the method for target fusion detection in the dual band IR images by implementing experiments using the real dual band IR image sequences in detail. Experimental results indicated that the proposed background suppression and target enhancing algorithm gained significant performance improvement for target detection in highly clutter IR images with low signal to noise ratio and improved the system＇s performance for target detection to a great degree by the dual band IR images.