Abstract
Infrared (IR) small target detection has always been a challenging task due to its characteristics and the associated complex background. The existing methods have some issues with detection in a complex background. To improve the existing methods, target detection based on fractional directional derivative (FDD) and phase Fourier transform (PFT) is proposed. The first stage can effectively suppress the clutter background using FDD, and in the second stage, the saliency detection method computes the saliency maps detect the targets. Results from experiments indicate that the method proposed here reduce the background noise and also detect the target accurately as well.
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The authors would like to thank all the valuable reviewers.
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Rawat, S.S., Verma, S.K., Kumar, Y. (2021). Infrared Small Target Detection Based on Fractional Directional Derivative and Phase Fourier Spectrum Transform. In: Jeena Jacob, I., Kolandapalayam Shanmugam, S., Piramuthu, S., Falkowski-Gilski, P. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-8530-2_46
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DOI: https://doi.org/10.1007/978-981-15-8530-2_46
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