Enhancing Underwater Image via Adaptive Color and Contrast Enhancement, and Denoising

TL;DR

This paper introduces a novel adaptive color, contrast enhancement, and denoising framework for underwater images, significantly improving visibility, color accuracy, and detail preservation compared to existing methods.

Contribution

The paper presents a new ACCE-D framework combining adaptive variational enhancement and noise suppression using filters, with a pyramid-based solution for efficient underwater image enhancement.

Findings

Effective color correction and contrast enhancement demonstrated.

Superior performance over state-of-the-art techniques in experiments.

Applicable to other degraded scenes like foggy and low-light environments.

Abstract

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.