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作 者:金维维 华臻[1] 冯巍巍 王伟亭 李振忠 刘辉[2] Jin Weiwei;Hua Zhen;Feng Weiwei;Wang Weiting;Li Zhenzhong;Liu Hui(School of Information and Electronic Engineering,Shandong Technology and Business University,Yantai 264003,Shandong,China;CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation/Yantai Institute of Coastal Zone Research,Chinese Academy of Sciences,Yantai 264003,Shandong,China;University of Chinese Academy of Sciences,Beijing 100049,China)
机构地区:[1]山东工商学院信息与电子工程学院,山东烟台264003 [2]中国科学院海岸带环境过程与生态修复重点实验室(烟台海岸带研究所),山东烟台264003 [3]中国科学院大学,北京100049
出 处:《计算机应用与软件》2021年第9期239-243,255,共6页Computer Applications and Software
基 金:国家重点研发计划项目(2016YFC1400601);中国科学院关键技术人才项目(科发人函字[2016]65号);烟台市重点研发计划项目(2016ZH071);中国科学院STS项目(KFJ-STS-ZDTP-055)。
摘 要:为了实现海洋牧场典型物种(海参)的自动识别,利用多尺度retinex算法对其进行处理。在此算法的基础上,针对水下图像的成像特点,提出改进型多尺度retinex的计算方法。对亮度分量做多尺度增强处理,求出原图各彩色通道与亮度分量的比值;根据比值重新确定各彩色通道的灰度值;为了改善对比度,对每个通道进行分段线性拉伸;经过对比度受限的自适应直方图均衡化。利用建立的新算法对水下图像进行处理。结果表明,该算法能更有效地去除蓝绿色偏,提高图像的对比度,可以为水下海参自动捕捞设备的研制提供新的计算方法。In order to realize the automatic identification of typical species of marine ranching(sea cucumber),the multi-scale retinex algorithm is used to process this problem.Based on this algorithm,an improved multi-scale retinex calculation method is proposed for the imaging characteristics of underwater images.The luminance component was enhanced by multi-scale processing,and the ratio of each color channel of the luminance component of the original image was calculated.The gray value of each color channel was recalculated according to the ratio.In order to improve the contrast,divided linear strength was performed for each channel.The image was subjected to contrast-limited adaptive histogram equalization.Underwater images were processed with new algorithms.The results show that this algorithm can remove the blue-green bias more effectively and improve the contrast of the image,which can provide a new calculation method for the development of underwater sea cucumber automatic fishing equipment.
关 键 词:散射 水下图像增强 多尺度RETINEX算法 亮度分量
分 类 号:TP751[自动化与计算机技术—检测技术与自动化装置] TN911.73[自动化与计算机技术—控制科学与工程]
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