TY - JOUR
T1 - DRC
T2 - Chromatic aberration intensity priors for underwater image enhancement
AU - Liu, Qian
AU - He, Zongxin
AU - Zhang, Dehuan
AU - Zhang, Weishi
AU - Lin, Zifan
AU - Sohel, Ferdous
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China (No. 61702074 ), the Liaoning Provincial Natural Science Foundation of China (No. 20170520196 ), and the Fundamental Research Funds for the Central Universities, China (Nos. 3132019205 and 3132019354 ), the Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University , The 2022 National Undergraduate Innovation and Entrepreneurship Training Program project is the Marine Ranch Ecological Environment Visualization Monitoring System (project number: 202210577003 ). This work was supported in part by the High Performance Computing Center of Dalian Maritime University .
Publisher Copyright:
© 2024
PY - 2024/2
Y1 - 2024/2
N2 - Underwater imaging technology is a crucial tool for monitoring marine flora and fauna. However, selective light absorption and scattering properties of water make underwater imagery frequently appear blurred and exhibit color biases, hindering the extraction of vital aquacultural insights. To address this challenge, we propose a method, namely DRC, which is a holistic approach to enhancing underwater image clarity and color fidelity. This method comprises three integral components: D-procedure, R-procedure, and C-procedure. The D-procedure intricately accounts for the trichromatic underwater attenuation dynamics, formulating a chromatic aberration intensity prior. This prior counters the disparities in degradation levels seen in conventional single-channel prior depth estimations, achieving a dynamic depth representation approaching binocular image precision. The R-procedure, utilizing an adaptive dark-pixel prior, pinpoints corresponding points across varied depth zones to counteract backscattering, thereby mitigating the image's hazy appearance. The C-procedure bolsters image luminance and color fidelity through opponent channel rectification and amalgamates pronounced image contrasts and intricate details via Gaussian pyramid fusion. The method was tested on several publicly available datasets and compared with nine popular underwater image enhancement techniques. Both subjective and objective assessments underscore the superiority of our DRC method over existing underwater image enhancement techniques.
AB - Underwater imaging technology is a crucial tool for monitoring marine flora and fauna. However, selective light absorption and scattering properties of water make underwater imagery frequently appear blurred and exhibit color biases, hindering the extraction of vital aquacultural insights. To address this challenge, we propose a method, namely DRC, which is a holistic approach to enhancing underwater image clarity and color fidelity. This method comprises three integral components: D-procedure, R-procedure, and C-procedure. The D-procedure intricately accounts for the trichromatic underwater attenuation dynamics, formulating a chromatic aberration intensity prior. This prior counters the disparities in degradation levels seen in conventional single-channel prior depth estimations, achieving a dynamic depth representation approaching binocular image precision. The R-procedure, utilizing an adaptive dark-pixel prior, pinpoints corresponding points across varied depth zones to counteract backscattering, thereby mitigating the image's hazy appearance. The C-procedure bolsters image luminance and color fidelity through opponent channel rectification and amalgamates pronounced image contrasts and intricate details via Gaussian pyramid fusion. The method was tested on several publicly available datasets and compared with nine popular underwater image enhancement techniques. Both subjective and objective assessments underscore the superiority of our DRC method over existing underwater image enhancement techniques.
KW - Aquaculture
KW - Depth estimation
KW - Image enhancement
KW - Imaging model
KW - Underwater image
UR - https://www.scopus.com/pages/publications/85183456117
U2 - 10.1016/j.jvcir.2024.104065
DO - 10.1016/j.jvcir.2024.104065
M3 - Article
AN - SCOPUS:85183456117
SN - 1047-3203
VL - 98
JO - Journal of Visual Communication and Image Representation
JF - Journal of Visual Communication and Image Representation
M1 - 104065
ER -