Laser & Optoelectronics Progress, Volume. 57, Issue 12, 121016(2020)
Low-Illumination Underwater Image Enhancement Based on White Balance and Relative Total Variation
Fig. 2. Color correction results of low illumination underwater images. (a) Low illumination underwater images; (b) color correction results
Fig. 3. Estimation results of illuminance diagram. (a) Original image; (b) λ=0.01; (c) λ=0.02; (d) λ=0.03; (e) λ=0.04; (f) λ=0.05
Fig. 4. Comparison of enhancement results of each algorithm. (a) Original image; (b) CLAHE; (c) DCP; (d) Retinex; (e) Dehaze; (f) VCIP; (g) RTV; (h) our method
Fig. 5. Comparison of results based on SIFT application (the first group). (a) Original image; (b) CLAHE; (c) DCP; (d) Retinex; (e) Dehaze; (f) VCIP; (g) RTV; (h) our method
Fig. 6. Comparison of results based on SIFT application (the second group). (a) Original image; (b) CLAHE; (c) DCP; (d) Retinex; (e) Dehaze; (f) VCIP; (g) RTV; (h) our method
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Wei Zhang, Jichang Guo. Low-Illumination Underwater Image Enhancement Based on White Balance and Relative Total Variation[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121016
Category: Image Processing
Received: Sep. 9, 2019
Accepted: Nov. 2, 2019
Published Online: Jun. 3, 2020
The Author Email: Jichang Guo (jcguo@tju.edu.cn)