  Images captured underwater are often characterized by low contrast, color
distortion, and noise. To address these visual degradations, we propose a novel
scheme by constructing an adaptive color and contrast enhancement, and
denoising (ACCE-D) framework for underwater image enhancement. In the proposed
framework, Difference of Gaussian (DoG) filter and bilateral filter are
respectively employed to decompose the high-frequency and low-frequency
components. Benefited from this separation, we utilize soft-thresholding
operation to suppress the noise in the high-frequency component. Specially, the
low-frequency component is enhanced by using an adaptive color and contrast
enhancement (ACCE) strategy. The proposed ACCE is an adaptive variational
framework implemented in the HSI color space, which integrates data term and
regularized term, as well as introduces Gaussian weight and Heaviside function
to avoid over-enhancement and oversaturation. Moreover, we derive a numerical
solution for ACCE, and adopt a pyramid-based strategy to accelerate the solving
procedure. Experimental results demonstrate that our strategy is effective in
color correction, visibility improvement, and detail revealing. Comparison with
state-of-the-art techniques also validate the superiority of proposed method.
Furthermore, we have verified the utility of our proposed ACCE-D for enhancing
other types of degraded scenes, including foggy scene, sandstorm scene and
low-light scene.
