Improved Contrast Infrared Small Target Detection Algorithm Based on Local Edge Extraction

摘要

An algorithm of small and dim infrared target detection base on LCM (Local Contrast Method) combing with edge detection to solve the problem of high false alarm in small and dim infrared target detection under complex background. This algorithm firstly uses the LCM (Local Contrast Method) to extract the visual salient region in the image. Then the Canny operator is used to extract the edge of the cloud. The next we will get the local contrast map to compare with the result of Canny operator algorithm, the target which is located of the cloud edge will be eliminated. The last, adopt to threshold segmentation to separate the target. Analysis of the result shows that proposed algorithm which is based on LCM and Canny operator has a better detection result in small and dim infrared target detection under cloudy background. What's more, it can solve the problem of the high false alarm rate by LCM algorithm.