GithubHelp home page GithubHelp logo

hong-bo / fohis Goto Github PK

View Code? Open in Web Editor NEW

This project forked from noahzn/fohis

0.0 0.0 0.0 4.41 MB

Towards Simulating Foggy and Hazy Images and Evaluating their Authenticity

License: GNU General Public License v3.0

Python 100.00%

fohis's Introduction

Towards Simulating Foggy and Hazy Images and Evaluating their Authenticity

Ning Zhang, Lin Zhang*, and Zaixi Cheng

License:

This code is made publicly for research use only. 
It may be modified and redistributed under the terms of the GNU General Public License.
Please cite the paper and source code if you use it in your work.

@inproceedings{zhang2017towards,
title={Towards simulating foggy and hazy images and evaluating their authenticity},
author={Zhang, Ning and Zhang, Lin and Cheng, Zaixi},
booktitle={International Conference on Neural Information Processing},
pages={405--415},
year={2017},
organization={Springer}
}

Instructions:

This code has been tested in Windows10-64bit with Python3.4 installed.  
1. clone this project and put all the files in the same folder
2. folder structure:

      FoHIS/const.py  # define const
            fog.py  # main
            parameter.py # all parameters used in simulating fog/haze are defined here.
            tool_kit.py # some useful functions
            
      AuthESI/compute_aggd.py
              compute_authenticity.py  # main
              guided_filter.py  # some functions
              prisparam_16_hazeandfog.mat  # pre-trained model
              
      img/img.jpg  # RGB image
          imgd.jpg  # depth image
          result.jpg  # simulation
          
3. To simulate fog/haze effects:
    run python FoHIS/fog.py, the output 'result.jpg' will be saved in ../img/
      
4. To evaluate the authenticity:
    run python compute_authenticity.py to evaluate 'result.jpg' in ../img/

Dataset:

image

Source Image Maximum Depth Effect Homogeneous Particular Elevation
(a) 150 m Haze Yes No
(b) 400 m Haze Yes No
(c) 800 m Haze Yes No
(d) 30 m Fog Yes No
(e) 150 m Fog No Yes
(f) 30 m Fog+Haze No No
(g) 600 m Haze Yes No
(h) 400 m Haze Yes No
(i) 200 m Haze Yes No
(j) 100 m Haze Yes No
(k) 100 m Haze Yes No
(l) 800 m Fog+Haze No Yes
(m) 300 m Haze Yes No
(n) 60 m Haze Yes No
(o) 300 m Haze Yes No
(p) 1000 m Haze Yes No
(q) 400 m Haze Yes No
(r) 300 m Haze Yes No

fohis's People

Contributors

noahzn avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.