Optimization of Underwater Images Based on Gray World Algorithm and Jaffe-McGlamery Models
DOI:
https://doi.org/10.54097/papgd308Keywords:
Underwater Image Processing, Gray-world Algorithm, Jaffe-McGlamery Model, CLAHEAbstract
In this paper, a comprehensive scheme for underwater image processing is proposed based on the grayscale world algorithm and the Jaffe-McGlamery model. Firstly, a color bias detection based on grayscale world theory, a low light detection based on HSV color space, and a fuzzy detection method based on frequency domain and Laplace operator are designed to classify different types of image degradation. Subsequently, the corresponding scene degradation models are constructed for different degradation types through the simplified Jaffe-McGlamery model, and the image features under different water conditions are analyzed. Next, an improved gray world algorithm is used to eliminate color bias, the limiting contrast adaptive histogram equalization (CLAHE) technique is utilized to improve the image quality under low-light conditions, and the dark-channel a priori algorithm is optimized by the depth estimation and parameter adaptation modules to remove blurring. The proposed method in this study significantly improves the image quality in different scenarios and provides a new idea for underwater image processing.
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