Abstract
Underwater images are degraded mainly due to scattering and absorption effects but are key in oceanographic studies and research. Therefore, we need to develop methods that generate visually pleasing images and retain the original information. In this paper, we propose a method that chooses between Multiscale Fusion, Edge Preserving Decomposition-Based Haze Removal Algorithm or a combination of both. The algorithm that is to be used in an image is based on mean saturation value and fog density using Fog Aware Density Evaluator (FADE). The resulting image retains the natural color distribution, is dehazed and enhanced. The proposed algorithm doesn’t require prior hardware usage or prerequisite knowledge of the underwater environment. The proposed algorithm performs considerably well when compared to previous approaches against various image quality metrics such as UIQM, PCQI, PIQE, BRISQUE and Average Gradient.
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Paulson, R.M., Gopalakrishnan, S., Mahendiran, S., Srambical, V.P., Gopan, N.R. (2022). A Hybrid Fusion-Based Algorithm for Underwater Image Enhancement Using Fog Aware Density Evaluator and Mean Saturation. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1388. Springer, Singapore. https://doi.org/10.1007/978-981-16-2597-8_11
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DOI: https://doi.org/10.1007/978-981-16-2597-8_11
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