Analysis and selection of haze-relevant features for haze detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14771-w.pdf
Reference34 articles.
1. Akhtar F, Li J, Pei Y et al (2019) Optimal features subset selection for large for gestational age classification using gridsearch based recursive feature elimination with cross-validation scheme. In: International conference on frontier computing. Springer, pp 63–71
2. Ancuti CO, Ancuti C, Hermans C et al (2010) A fast semi-inverse approach to detect and remove the haze from a single image. In: Asian conference on computer vision. Springer, pp 501–514
3. Ancuti CO, Ancuti C, Timofte R (2020) Nh-haze: an image dehazing benchmark with non-homogeneous hazy and haze-free images. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops. pp 444–445
4. Chen B H, Huang S C, Cheng F C (2016) A high-efficiency and high-speed gain intervention refinement filter for haze removal. J Disp Technol 12 (7):753–759
5. Farge M (1992) Wavelet transforms and their applications to turbulence. Ann Rev Fluid Mech 24(1):395–458
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