Underwater image restoration based on adaptive parameter optimization of the physical model
Optics Express
|June 29, 2023
Summary
This study introduces an adaptive physical model for restoring degraded underwater images, enhancing color, contrast, and detail. The method effectively overcomes challenges posed by the complex marine environment for clearer visual data.
Area of Science:
- Computer Vision
- Image Processing
- Marine Technology
Background:
- Underwater images are crucial for marine data acquisition but suffer from degradation like color distortion, low contrast, and blur.
- Existing physical model-based methods struggle with the selective light absorption in water, limiting restoration effectiveness.
Purpose of the Study:
- To propose an adaptive physical model for effective underwater image restoration.
- To enhance color, contrast, and detail in degraded underwater images.
Main Methods:
- Adaptive color constancy algorithm to estimate background light.
- Smoothness and uniformity transmittance estimation to reduce halo and blur.
- Transmittance optimization for natural edge and texture smoothing.
- Integration with imaging model and histogram equalization for detail retention.
Main Results:
- Demonstrated significant advantages in color restoration, contrast enhancement, and overall image quality.
- Achieved remarkable results in application testing on the UIEBD dataset.
- Effectively eliminated image blurring and retained more image details.
Conclusions:
- The proposed adaptive physical model effectively restores degraded underwater images.
- Provides a theoretical foundation for advanced underwater imaging models.
- Offers improved visual data for marine information acquisition.
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