基于对比度受限直方图均衡化的水下海参图像增强方法

针对水下图像受到水下复杂光照的影响导致图像对比度差的现象,采用对比度受限自适应直方图均衡化方法（contrast-limited adaptive histogram equalization,CLAHE）对水下海参图像进行增强处理,算法首先将原始图像分割成若干个子区域并且大小相同,再选取特定值对每个子区域的直方图进行截取,并将截取下的像素均匀分配到每个灰度级,最终得到限定对比度直方图。并通过研究算法中的相关参数,得到适用于水下海参图像增强的参数值,取得了更好的增强效果。通过评价函数均方差（mean squared error,MSE）,峰值信噪比（peak signal to noise r...

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Bibliographic Details
Published in农业工程学报 Vol. 32; no. 6; pp. 197 - 203
Main Author 杨卫中 徐银丽 乔曦 饶伟 李道亮 李振波
Format Journal Article
LanguageChinese
Published 中国农业大学信息与电气工程学院,北京,100083%农业部农业信息技术重点实验室,北京,100083%北京农业物联网工程技术研究中心,北京,100083 2016
Subjects
动物
图像增强
机器人
水下图像
海参
直方图均衡
直方图均衡
机器人
image enhance
海参
undersea image
histogram equalization
水下图像
图像增强
动物
animals
robots
sea cucumber
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2016.06.027

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Summary:针对水下图像受到水下复杂光照的影响导致图像对比度差的现象,采用对比度受限自适应直方图均衡化方法（contrast-limited adaptive histogram equalization,CLAHE）对水下海参图像进行增强处理,算法首先将原始图像分割成若干个子区域并且大小相同,再选取特定值对每个子区域的直方图进行截取,并将截取下的像素均匀分配到每个灰度级,最终得到限定对比度直方图。并通过研究算法中的相关参数,得到适用于水下海参图像增强的参数值,取得了更好的增强效果。通过评价函数均方差（mean squared error,MSE）,峰值信噪比（peak signal to noise rate,PSNR）和信息熵（information entropy）对比CLAHE方法和其他一些方法,结果显示CLAHE算法在水下海参图像提高质量和保持图像细节方面表现出更好的性能,为以后水下机器人的识别定位提供了方便。
Bibliography:11-2047/S
image enhance; animals; robots; undersea image; sea cucumber; histogram equalization
Because of the suspended solids in the underwater environment, and light absorption and scattering, underwater sea cucumber image has the weaknesses of illumination uneven, low contrast, various kinds of noise and soon, causing difficulties for the identification for underwater robots. In this paper, image enhancement technology for underwater sea cucumber image was studied, and a method called Contrast-limited Adaptive Histogram Equalization（ CLAHE） was proposed to deal with the underwater sea cucumber images. We used sea cucumbers which grew up in Shandong Haiyang Thousand-Island Lake aquaculture base as the experimental subject, and recorded video by artificial dive underwater with the digital camera（Canon Power Shot G12） in July 2015, in order to get all kinds of images（single sea cucumber, sea cucumber with substrates, many sea cucumbers） filtrated the pictures from all the videos, at last we got about 200 images
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.06.027