Infrared dim and small target background suppression based on improved gradient inverse weighting filter

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Dim and small infrared target easily flooded in complicated background. In order to improve the ability of target detection, the background is often suppressed to enhance the target signal. Referring to the lack of robust adaptability of the gradient inverse weighted filtering for background edges , an improved gradient inverse weighting filtering algorithm is proposed through the establishment of background local correlation function. The use of background local statistical characteristics of adaptive filter parameters, can better adapt to the drastic change in the background, and improve the ability to suppress background suppression algorithm. Experimental results show that the improved gradient inverse weighted filtering could effectively suppress the background of images, presenting a superior overall performance to other background suppression methods.