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Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising

机译:通过光学成像模型和非局部均值去噪增强水下彩色图像

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This paper proposes a novel framework for enhancing underwater images captured by optical imaging model and non-local means denoising. The proposed approach adjusts the color balance using biasness correction and the average luminance. Scene visibility is then enhanced based on an underwater optical imaging model. The increase in noise in the enhanced images is alleviated by non-local means (NLM) denoising. The final enhanced images are characterized by improved visibility while retaining color fidelity and reducing noise. The proposed method does not require specialized hardware nor prior knowledge of the underwater environment.
机译:本文提出了一个新的框架,用于增强光学成像模型和非局部去噪技术所捕获的水下图像。所提出的方法使用偏差校正和平均亮度来调整色彩平衡。然后基于水下光学成像模型来增强场景可见性。增强图像中噪声的增加通过非局部均值(NLM)降噪得到缓解。最终的增强图像的特点是提高了可见度,同时保留了色彩保真度并减少了噪点。所提出的方法不需要专门的硬件或水下环境的先验知识。

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