Detection of Aerial Dim Small Targets in Infrared Images based on Mathematical Morphology

Infrared target detection is a crucial step in many fields of infrared image and video processing. It plays an important role in military and surveillance applications. The aerial infrared target region usually has a small size and is embedded in a cluttered background. Therefore, very limited shape information and low signal to noise ratio (SNR) are the typical properties of aerial infrared targets. For the detection step, the paper idea is based on enhancing the dim small targets by applying Kim’s LoG filter and modifying New Top Hat transformation (NTH). Therefore, it improves the contrast ratio between the target and background region. Experimental results exhibit the ability of the new algorithm for application of aerial infrared target detection. The evaluated performances demonstrate that the suggested algorithm is more efficient compared with some widely used methods.