研究目的
To define an effective methodology for the performance evaluation of underwater image enhancement techniques and to guide the underwater community in choosing the best method for different underwater conditions.
研究成果
The study concludes that the ACE algorithm performs well in various environmental conditions, while CLAHE and SP can produce good enhancements in some conditions. The LAB algorithm slightly improves 3D reconstruction results. The E metric is recommended for objective evaluation as it is consistent with expert panel evaluations.
研究不足
The study is limited to five selected image enhancement methods and a specific dataset of underwater images. The evaluation metrics may not fully capture the performance of the methods in all possible underwater conditions.
1:Experimental Design and Method Selection:
Selected five well-known methods from the state of the art for underwater image enhancement.
2:Sample Selection and Data Sources:
Assembled a heterogeneous dataset of images from various underwater sites with different conditions of depth, turbidity, and lighting.
3:List of Experimental Equipment and Materials:
Used different cameras and resolutions for image acquisition.
4:Experimental Procedures and Operational Workflow:
Enhanced the dataset images with each of the selected algorithms and evaluated them using three different approaches: objective metrics, expert panel evaluation, and 3D reconstruction results.
5:Data Analysis Methods:
Employed quantitative metrics for objective evaluation, ANOVA for expert panel evaluation, and Cloud Compare software for 3D reconstruction evaluation.
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