2024年1月13日发(作者：旅小凝)
信息技术Doi:
10.19661/.2020.04.005!借息技术】水下视觉SLAM图像增强研究张阳%.
2,
*,徐爽0,朱建军%，2,
3,李海森%，2,
*(1.哈尔滨工程大学水声技术重点实验室哈尔滨15000%；
2.海洋信息获取与安全工信部重点实验室工业和信息化部哈尔滨％5000%；
3.哈尔滨工程大学水声工程学院哈尔滨％5000%；4.中国石油集团工程技术研究有限公司天津30045%)摘要针对水下图像质量降低导致视觉SLAM中图像特征点提取与匹配数量减少的情况，提出一种采用图像增强算
法改善对比度提高图像特征匹配数量的方法。本文分析了水下图像在水体吸收和散射作用下导致图像质量下降，以及
由此造成的视觉SLAM定位精度降低的原因。对比了空域和频域图像增强算法，选择直方图均衡化作为图像预处理方
法，研究了直方图均衡化过程。在实际海域分别采集了对比度不同的两组图像，利用ORB特征法进行特征提取与匹
配。实验表明，图像增强对水下图像特征点提取、匹配数量以及正确匹配数量均具有较大改善，特别是对比度不高的
图像，效果更为明显。关键词水下视觉；SLAM；图像增强；特征提取；特征匹配中图分类号P229Underwater
Visual
SLAM
Image
Enhancement
ResearchZHANG
Yang%，2,
3,
XU
Shuang4,
ZHU
Jianjun%，2,
3,
LI
Haisen%，2,
3(%.
Acoustic Science
and
Technology
Laboratory,
Harbin
Engineering
University,
Harbin
15000%,
China;2.
Key
Laboratory
of
Marine
Information
Acquisition
and
Security
(Harbin
Engineering
University),
Ministry
of
Industry
andInformation
Technology,
Harbin
15000%,
China;
3.
College of
Underwater
Acoustic
Engineering,
Harbin
Engineering
University,Harbin
%5000%,
China;
4.
Research
Institute
of
Engineering
Technology,
CNPC,
Tianjin
30045%,
China)Abstract
Against
the
reduced
number
of
feature
points
extracted
and
matched
in
visual
SLAM
due
to
the
degradation
of
underwater
image
quality, a
method
using
image
enhancement
algorithms
to
improve
the
contrast
and
increase
the
number
of
feature
matches
in
the
image
was
proposed.
This
paper
analyzes
the
reasons
for
the
degradation
of
the
image
quality
caused
by
the
absorption
and
scattering
of
water
in
the
underwater
image,
and
the
reasons
for
the
decline
in
the
accuracy
of
the
visual
SLAM
positioning.
The
spatial
and
frequency
domain
image
enhancement
algorithms
are
compared.
Histogram
equalization
is
selected
as
the
image
preprocessing
method,
and
the
histogram
equalization
process
is
studied.
Two
sets
of
images
with
different
contrast
were
collected
in
the
actual
sea
area,
and
the
features
were
extracted
and
matched
using
the
ORB
feature
method.
Experiments
show
that
image
enhancement
has
greatly
improved
the
feature
point
extraction,
the
number
of
matches,
and
the
number
of
correct
matches
in
underwater
images,
especially for
images with
low
ds
underwater
visual;
SLAM;
image
enhancement;
feature
extraction;
feature
matching收稿日期：2020-09-0%项目支撑：国家重点研发计划项目(2017YFC0306000)；国家重点研发计划项目(20%,Y(F02%2203)；深水油气开发海工关键技术研
究(20%9A-%0%%)$||海洋信2020年第4期29
||
2024年1月13日发(作者：旅小凝)
信息技术Doi:
10.19661/.2020.04.005!借息技术】水下视觉SLAM图像增强研究张阳%.
2,
*,徐爽0,朱建军%，2,
3,李海森%，2,
*(1.哈尔滨工程大学水声技术重点实验室哈尔滨15000%；
2.海洋信息获取与安全工信部重点实验室工业和信息化部哈尔滨％5000%；
3.哈尔滨工程大学水声工程学院哈尔滨％5000%；4.中国石油集团工程技术研究有限公司天津30045%)摘要针对水下图像质量降低导致视觉SLAM中图像特征点提取与匹配数量减少的情况，提出一种采用图像增强算
法改善对比度提高图像特征匹配数量的方法。本文分析了水下图像在水体吸收和散射作用下导致图像质量下降，以及
由此造成的视觉SLAM定位精度降低的原因。对比了空域和频域图像增强算法，选择直方图均衡化作为图像预处理方
法，研究了直方图均衡化过程。在实际海域分别采集了对比度不同的两组图像，利用ORB特征法进行特征提取与匹
配。实验表明，图像增强对水下图像特征点提取、匹配数量以及正确匹配数量均具有较大改善，特别是对比度不高的
图像，效果更为明显。关键词水下视觉；SLAM；图像增强；特征提取；特征匹配中图分类号P229Underwater
Visual
SLAM
Image
Enhancement
ResearchZHANG
Yang%，2,
3,
XU
Shuang4,
ZHU
Jianjun%，2,
3,
LI
Haisen%，2,
3(%.
Acoustic Science
and
Technology
Laboratory,
Harbin
Engineering
University,
Harbin
15000%,
China;2.
Key
Laboratory
of
Marine
Information
Acquisition
and
Security
(Harbin
Engineering
University),
Ministry
of
Industry
andInformation
Technology,
Harbin
15000%,
China;
3.
College of
Underwater
Acoustic
Engineering,
Harbin
Engineering
University,Harbin
%5000%,
China;
4.
Research
Institute
of
Engineering
Technology,
CNPC,
Tianjin
30045%,
China)Abstract
Against
the
reduced
number
of
feature
points
extracted
and
matched
in
visual
SLAM
due
to
the
degradation
of
underwater
image
quality, a
method
using
image
enhancement
algorithms
to
improve
the
contrast
and
increase
the
number
of
feature
matches
in
the
image
was
proposed.
This
paper
analyzes
the
reasons
for
the
degradation
of
the
image
quality
caused
by
the
absorption
and
scattering
of
water
in
the
underwater
image,
and
the
reasons
for
the
decline
in
the
accuracy
of
the
visual
SLAM
positioning.
The
spatial
and
frequency
domain
image
enhancement
algorithms
are
compared.
Histogram
equalization
is
selected
as
the
image
preprocessing
method,
and
the
histogram
equalization
process
is
studied.
Two
sets
of
images
with
different
contrast
were
collected
in
the
actual
sea
area,
and
the
features
were
extracted
and
matched
using
the
ORB
feature
method.
Experiments
show
that
image
enhancement
has
greatly
improved
the
feature
point
extraction,
the
number
of
matches,
and
the
number
of
correct
matches
in
underwater
images,
especially for
images with
low
ds
underwater
visual;
SLAM;
image
enhancement;
feature
extraction;
feature
matching收稿日期：2020-09-0%项目支撑：国家重点研发计划项目(2017YFC0306000)；国家重点研发计划项目(20%,Y(F02%2203)；深水油气开发海工关键技术研
究(20%9A-%0%%)$||海洋信2020年第4期29
||