Abstract
The majority of the existing methods for image dehazing are of more complexity, which exhibits more time for execution. Therefore, these algorithms may not be suitable for real-time image processing systems. Also, the existing methods do not consider the local variations of the hazy image that may result in over-saturation and under-saturation. Hence, there is a requirement to design a fast dehazing algorithm that adaptively dehazes according to the local region characteristics. In the proposed technique, a hazy image is first classified into ‘less-affected by haze’ and ‘more-affected by haze’ regions, on the basis of pixel intensity values. The image decomposition, image dehazing, and details enhancement are implemented separately in two blocks, namely ‘less-affected by haze’ and ‘more-affected by haze’ blocks, with different scale factors for adaptive dehazing. The results of these two blocks are fused based upon the regional categorization. The proposed algorithm produces good dehazed results at the rate of 25 frames per second.
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Kumar, B.P., Kumar, A., Pandey, R. (2023). Fast Adaptive Image Dehazing and Details Enhancement of Hazy Images. In: Yadav, R.P., Nanda, S.J., Rana, P.S., Lim, MH. (eds) Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-8742-7_18
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DOI: https://doi.org/10.1007/978-981-19-8742-7_18
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