研究目的
To develop a new restoration model for underwater images that enhances clarity and colorfulness, specifically for turbid offshore environments, by using reflection-illumination decomposition and local backscattering lighting estimation.
研究成果
The proposed method effectively restores offshore underwater images by leveraging optical priors and reflection-illumination decomposition, achieving superior clarity and color restoration compared to existing algorithms. It demonstrates wide applicability and significant improvements in image quality metrics, with potential for extension to other water types with appropriate priors.
研究不足
The method is specifically designed for offshore underwater images with high concentrations of tripton and cDom; performance may vary in other water types. Computational time, though improved, could be further optimized for real-time applications. The reliance on empirical parameters and priors may limit generalizability to all underwater conditions.
1：Experimental Design and Method Selection:
The methodology involves designing an underwater image restoration algorithm based on the dark channel prior, incorporating reflection-illumination decomposition for transmission map estimation and local Gaussian backscattering light estimation. Theoretical models include the Jaffe-McGlamery underwater imaging model and Retinex theory.
2：Sample Selection and Data Sources:
300 RGB underwater images collected from online sources related to offshore investigation, sea farming, and coastal areas, with sizes ranging from 194x259 to 3968x2976 pixels.
3：List of Experimental Equipment and Materials:
A tank (2.53 m long, 1.02 m wide, 1.03 m high), OTI-UWC-325/P/E color camera, Imatest 4.3 SFR chart, ColorChecker 24 X-Rite Chart, and software tools like Matlab 2016a for implementation.
4：53 m long, 02 m wide, 03 m high), OTI-UWC-325/P/E color camera, Imatest 3 SFR chart, ColorChecker 24 X-Rite Chart, and software tools like Matlab 2016a for implementation.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Steps include computing the dark channel image, estimating the transmission map using Retinex decomposition, estimating backscattering light with Gaussian filtering, restoring the image using the underwater imaging model, and applying color correction and saturation adjustment.
5：Data Analysis Methods:
Quantitative evaluation using metrics such as contrast, saturation, chroma variance, and UCIQE (Underwater Color Image Quality Evaluation), as well as subjective inspection and comparisons with state-of-the-art methods.
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