Underwater Image Enhancement and Attenuation Restoration Based on Depth and Backscatter Estimation

IF 4.2 2区计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Computational Imaging Pub Date : 2025-02-20 DOI:10.1109/TCI.2025.3544065

Yi-Zeng Hsieh;Ming-Ching Chang

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引用次数: 0

Abstract

Underwater image analytic technologies is important to study in-water imagery in oceanography. Due to the poor lighting conditions and severe scattering and attenuation of light, underwater image quality is heavily reduced in such environment. Therefore, underwater image enhancement has always been an essential step in the analysis pipeline. We develop an Underwater Image Enhancement and Attenuation Restoration (UIEAR) algorithm from a RGB image input based on 3D depth and backscatter estimation. The proposed underwater image enhancement method achieves superior performance with light computational requirements, making it easy to deploy on edge devices. We provide the following contributions: (1) Our image enhancement is based on depth estimation using a new smooth operator on RGB pixels, which provides 3D spatial information for improved backscatter estimation and attenuation restoration. (2) We develop an improved imaging model by considering parameters relative to the camera and the local light source to estimate the attenuation and the backscatter effects. Our light source estimation is constructed from a local neighborhood of pixels to avoid distortion of the backscatter and attenuation estimation. (3) We adopt white balance adjustment to enhance underwater pixels and better match real-world colors. Our method improves general underwater image analysis including object detection and segmentation. Experimental results demonstrate the effectiveness of our algorithm in restoring and enhancing underwater images.

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基于深度和后向散射估计的水下图像增强与衰减恢复

水下图像分析技术是海洋学研究水中图像的重要手段。由于光照条件差，光线散射和衰减严重，在这种环境下，水下图像质量严重下降。因此，水下图像增强一直是分析流水线中必不可少的一步。我们开发了一种基于三维深度和后向散射估计的RGB图像输入的水下图像增强和衰减恢复（UIEAR）算法。本文提出的水下图像增强方法具有优异的性能和较轻的计算需求，易于在边缘设备上部署。我们提供了以下贡献：(1)我们的图像增强基于深度估计，使用新的RGB像素平滑算子，为改进的后向散射估计和衰减恢复提供了三维空间信息。(2)建立了一种改进的成像模型，考虑了与相机和局部光源相关的参数来估计衰减和后向散射效应。我们的光源估计是由像素的局部邻域构造的，以避免后向散射和衰减估计的失真。(3)我们采用白平衡调整来增强水下像素，更好地匹配真实世界的颜色。该方法改进了一般的水下图像分析，包括目标检测和分割。实验结果表明，该算法对水下图像的恢复和增强是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Computational Imaging Mathematics-Computational Mathematics

CiteScore

8.20

自引率

7.40%

发文量

期刊介绍： The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs. Topics of interest will include advanced algorithms and mathematical techniques, model-based data inversion, methods for image and signal recovery from sparse and incomplete data, techniques for non-traditional sensing of image data, methods for dynamic information acquisition and extraction from imaging sensors, software and hardware for efficient computation in imaging systems, and highly novel imaging system design.