Abstract
Robust small target detection of infrared clutter background has drawn great interest of scholars. Recently, morphological filter is playing a significant role in detecting infrared point target. Generally, the background clutter and targets are diverse in the case of each image. Traditional fixed structural elements cannot acquire to successful point target detection in complex background. Therefore, a new method is introduced based on quantum genetic algorithm to optimize and obtain structural element which is used as morphological filter for point target detection in original Infrared images. Then, morphological contrast operation is proposed to enhance areas of point targets after the filtered image is obtained. Thus, an enormous background clutter and noise are suppressed and the contrast between target and background are observably increased. Finally, by setting proper threshold, the point targets can be detected perfectly. Experimental evaluation results show that the proposed method is effective and robust with respect to detection accuracy.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, G., Hamdulla, A. (2019). Point Target Detection Based on Quantum Genetic Algorithm with Morphological Contrast Operation. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_44
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DOI: https://doi.org/10.1007/978-3-030-32216-8_44
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