Maritime surveillance systems’ long-range capabilities are dependent on the quality of their images. Poor weather conditions such as haze, fog, or smog can severely hamper the ability to observe a thermal imaging scenario accurately, which affects the ability to detect, identify and track any object of interest within it. An image processing technique, known as dehazing is required in these types of systems. In this paper, state of the art image dehazing algorithms are used for long range thermal images (~5km, ~9km, ~15km) and their image restoration quality performances are compared based on qualitative metrics such as structural similarity (SSIM), peak signal to noise ratio (PSNR), and Feature similarity (FSIM). The results from this benchmark study can provide a suitable dehazing technique for maritime surveillance systems.
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