An Image Enhancement Algorithm for Autonomous Underwater Vehicles: A Novel Approach
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3611-3_41
Reference8 articles.
1. Wu, X. J., & Li, H. S. (2013). A simple and comprehensive model for underwater image restoration. In 2013 IEEE International conference on information and automation, ICIA 2013 (pp. 699–704). https://doi.org/10.1109/ICInfA.2013.6720385
2. Panetta, K., Gao, C., Agaian, S. (2015). Human-visual-system-inspired underwater image quality measures. Image enhancement for IEEE Journal of Oceanic Engineering, 41(3), 541–551.
3. Lu, H., Serikawa, S. (2014). A novel underwater scene reconstruction method. In Proceedings–2014 International Symposium on Computer, Consumer and Control, IS3C 2014 (pp. 773–775)
4. Galdran, A., Pardo, D., Picón, A., Alvarez-Gila, A. (2015). Automatic red-channel underwater image restoration. Journal of Visual Communication and Image Representation 26, 132–145. https://doi.org/10.1016/j.jvcir.2014.11.006
5. Perez, J., Sanz, P. J., Bryson, M., Williams, S. B. (2017). A benchmarking study on single image dehazing techniques for underwater autonomous vehicles. In OCEANS 2017
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