Abstract

This paper investigates an adaptive method of dim small target detection in infrared images with a complex background. We analyze in depth the characteristics of the background, the target, and the noise in the gray intensity, space and frequency domain of the images. The modified top-hat transformation using interrelated structuring elements is adopted to adaptively detect the darker and the brighter targets and greatly suppress the cluttered background. Lateral pattern inhibition enhances the local contrast ratio and simultaneously identifies the targets of interest. The automatic threshold is used to enhance real dim targets in the cluttered background. A simulation based on the proposed algorithm is carried out and the results prove that the algorithm is effective and valid.

© 2013 Optical Society of America

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