Underwater Color Enhancement Method

Dartmouth Reality and Robotics Lab

Authors: Monika Roznere and Alberto Quattrini Li

NOTE: Current application should work well. There are some small issues that need to dealt with, see below.

Related Publications

M. Roznere and A. Quattrini Li, “Real-time model-based image color correction for underwater robots,” IROS, 2019. PDF

License

If you use our underwater color enhancement application in an academic work, please cite:

@inproceedings{RoznereColor2019,
  title={Real-time Model-based Image Color Correction for Underwater Robots},
  author={Monika Roznere and Alberto {Quattrini Li}},
  booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2019}
 }

Work in Progress

Overall:

• Time optimize color enhancement.
  • Currently it takes ~7 ms to enhance an image (1920 x 1080).

New Model Method:

• Wideband veiling light [FUTURE]:
  • Calculate average background pixel using image processing

Getting Started

This package has been tested on Ubuntu 16.04.

Set up your catkin workspace

mkdir -p catkin_ws/src
cd catkin_ws/src/
catkin_init_workspace

Install

Clone repository:

git clone https://github.com/dartmouthrobotics/underwater_color_enhance

Clone and build this repository as well:

• modified monocular ORB-SLAM

git clone https://github.com/dartmouthrobotics/ORB_SLAM2
cd ORB_SLAM2/
cd Thirdparty/
git clone https://github.com/stevenlovegrove/Pangolin
cd Pangolin/
mkdir build
cd build/
cmake ..
cmake --build .
cd ../../../
chmod +x build.sh
./build.sh
export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:$(pwd)/Examples/ROS/ORB_SLAM2ROS
chmod +x build_ros.sh
./build_ros.sh

Third-party Packages

Run:

cd underwater_color_enhance/
mkdir third-party
cd third-party/

In the third-party directory, clone these repositories:

• yaml-cpp

git clone https://github.com/jbeder/yaml-cpp
git clone https://github.com/wxFormBuilder/ticpp
git clone https://github.com/davisking/dlib

• ticpp

• dlib

Build

catkin_make
source devel/setup.bash

Configuration

config/image_config.yaml (note all paths are with respect to $ROOT_PATH, see image_color_enhance.launch):

• image: <path to single input image>
  
  

• distance: <from the camera to the object of interest, in meters>

• depth: <altitude depth; positive value, in meters>

• camera_response_filename: <path to camera response file>

  • Sony_IMX322LQJ-C_Camera_Response.csv is the USB camera used on the BlueROV2.

• jerlov_water_filename: <path to jerlov water properties file>

• water_type: <define approximate type of water the image was taken in>
  
  

• method: <0: A Revised Underwater Image Formation Model>
  
  

• color_1_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]

• color_2_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]
  
  

• est_veiling_light: <true: uses background sample to calculate average wideband veiling light | false: calculate wideband veiling light>

• background_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]
  
  

• show_image: <true/false: shows raw and color corrected image>

• check_time: <true/false: track and print to screen time latency at different points>

• log_screen: <true/false: log to screen debug messages>
  
  

• save_data: <true/false: attenuation values saved to 'output_filename' or not>

• prior_data: <true/false: attenuation values used from 'input_filename' or not>

• output_filename: <xml file to save attenuation values with its depth measurement>

• input_filename: <xml file to load attenuation values with its depth measurement>

config/ros_config.yaml:

Note: optimize option will not color correct any images. Instead it will go through and calculate optimized attenuation values, which can then be used later through the prior data option.

• camera_topic: <topic name for the camera image messages>

• depth_topic: <topic name for the altitude depth messages>
  
  

• distance: <from the camera to the object of interest, in meters>

• camera_response_filename: <path to camera response file>

  • Sony_IMX322LQJ-C_Camera_Response.csv is the USB camera used on the BlueROV2.

• jerlov_water_filename: <path to jerlov water properties file>

• water_type: <define approximate type of water the image was taken in>
  
  

• method: <0: A Revised Underwater Image Formation Model>
  
  

• optimize: <true: optimize attenuation values in depth range | false: calculate attenuation values per image frame>

• range: <depth intervals for optimizing attenuation values>
  
  

• slam_input: <true/false: distance values are used from monocular ORB-SLAM features>
  
  

• color_1_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]

• color_2_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]
  
  

• est_veiling_light: <true: uses background sample to calculate average wideband veiling light | false: calculate wideband veiling light>

• background_sample: [<x-coordinate>, <y-coordinate>, <width of region>, <height of region>]
  
  

• show_image: <true/false: shows raw and color corrected image>

• check_time: <true/false: track and print to screen time latency at different points>

• log_screen: <true/false: log to screen debug messages>
  
  

• save_data: <true/false: attenuation values saved to 'output_filename' or not>

• prior_data: <true/false: attenuation values used from 'input_filename' or not>

• output_filename: <xml file to save attenuation values with its depth measurement>

• input_filename: <xml file to load attenuation values with its depth measurement>

Run

For one image (no ROS implementation), based on the parameters in image_config.yaml:

roslaunch underwater_color_enhance image_color_enhance.launch

For rosbag files, based on the parameters in ros_config.yaml:

roslaunch underwater_color_enhance ros_color_enhance.launch