  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, Gaussian 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. Accordingly, the low-frequency component is enhanced
by using an adaptive color and contrast enhancement (ACCE) strategy. The
proposed ACCE is a new adaptive variational framework implemented in the HSI
color space, in which we design a Gaussian weight function and a Heaviside
function to adaptively adjust the role of data item and regularized item.
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 propose 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.
