长江信息通信2024,Vol.37Issue(8) :107-110.DOI:10.20153/j.issn.2096-9759.2024.08.032

基于水下目标识别精度的图像增强算法研究

Research on Image Enhancement Algorithm Based on Underwater Target Recognition Accuracy

文英铭 雷彦琨
长江信息通信2024,Vol.37Issue(8) :107-110.DOI:10.20153/j.issn.2096-9759.2024.08.032

基于水下目标识别精度的图像增强算法研究

Research on Image Enhancement Algorithm Based on Underwater Target Recognition Accuracy

文英铭 1雷彦琨1
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作者信息

  • 1. 大连大学信息工程学院,辽宁大连 116622
  • 折叠

摘要

针对水下光线吸收导致水下图像模糊、产生色偏;水下生物姿态不同、相互遮挡导致目标识别精确率下降问题,使用RGHS图像增强、IBLA色域调节、调节锐化值、对比度参数4种方法处理数据集内图像,以恢复图像原色彩、还原图像细节从而提升识别精确率.实验表明,对图像处理可以有效提升识别精确率,将4种图像处理方法有机结合,证明使用多种图像处理方法可以提升识别精确率,对于均衡总体识别精确率,使用IBLA色域调节即可;对于不同的生物,也给出适合使用的图像处理结合方案.

Abstract

Aiming at the blurring and color deviation of underwater images caused by underwater light absorption;The problem of decreased accuracy in target recognition due to different poses and mutual occlusion of underwater organisms is addressed by using four methods:RGHS im-age enhancement,IBLA color gamut adjustment,sharpening value adjustment,and contrast pa-rameter to process images in the dataset,in order to restore the original color of the image,re-store image details,and improve recognition accuracy.Experiments have shown that image pro-cessing can effectively improve recognition accuracy.By organically combining four image pro-cessing methods,it has been proven that using multiple image processing methods can improve recognition accuracy.For balanced overall recognition accuracy,using the IBIA color gamut ad-justment is sufficient;Suitable image processing combination schemes are also provided for dif-ferent organisms.

关键词

RGHS/IBLA/YOLOv5

Key words

RGHS/IBLA/YOLOv5

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出版年

2024
长江信息通信
湖北通信服务公司

长江信息通信

影响因子:0.338
ISSN:2096-9759
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