为提高舰员对舰船的维修保障能力，尤其是舰船水下部分及附属装置的检查、清洗、切割或维修等，需借助水下视觉辅助设备，但利用视觉设备在水下所取得的图像存在着清晰度低模糊、色偏严重对比度不高、亮度偏暗等缺点。为解决这一问题，在深入分析常用图像增强算法的基础上，经过筛选采用改进后的暗通道优先算法对水下图像进行增强，提高水下图像的对比度和对水下图像进行颜色校正，以适应人眼对图像信息的获取。首先使用传统的暗通道先验算法对图像颜色校正，使图像看起来颜色更加均匀对比度更高，随后利用改进的暗通道先验算法进行改进。改进后的算法模型传输率更高，PSNR更均衡，图片中噪声更小，更清晰，可以满足水下图像的观测要求，为实际舰船水下检修提供可靠的帮助。
In order to improve the maintenance support ability of shipmen to ships, especially the inspection, cleaning, cutting or maintenance of underwater parts and auxiliary devices of ships, and underwater visual aids are needed. In view of the shortcomings of underwater images, such as low definition, fuzzy, serious color deviation, low contrast, dark brightness and so on. Based on the in-depth analysis of common image enhancement algorithms, after screening, the improved dark channel first algorithm is used to enhance the underwater image, improve the contrast of underwater image and correct the color of underwater image to adapt to the acquisition of image information by human eyes. Firstly, the traditional dark channel a priori algorithm is used to correct the image color, so that the image looks more uniform and has higher contrast. Then the dark channel prior algorithm is improved, and the transmission rate of the improved algorithm model is higher, PSNR is more balanced, the noise in the picture is smaller and clearer, which can meet the observation requirements of underwater images.
2022,44(23): 132-136 收稿日期：2021-10-26
DOI：10.3404/j.issn.1672-7649.2022.23.026
分类号：TP391.41
基金项目：海军工程大学科研自主立项项目
作者简介：伍哲(1992-)，男，硕士研究生，助教，研究方向为机器人水下视觉
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