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Research paper Implementation: Natural-based underwater image color enhancement through fusion of swarm-intelligence algorithm

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Underwater-image-color-enhancement-with-PSO-python-implementation

Implemented the research paper, Natural-based underwater image color enhancement through fusion of swarm-intelligence algorithm in python language.

The Four steps strategy followed in NUCE method:

  • Superior based underwater color cast neutralization
  • Dual-intensity images fusion based on average of mean and median values
  • Swarm-intelligence based mean equalization
  • Unsharp masking

Image credits: paper

User Guide

  • Clone this repository
$ git clone https://github.com/prashamsatalla/Underwater-image-color-enhancement-with-PSO-python-implementation.git
$ cd Underwater-image-color-enhancement-with-PSO-python-implementation
  • Collect input images in images folder, then the enhanced output image will be saved in results folder with respective input image name.
  • Install required packages
$ pip install -r requirements.txt
  • Run main.py .
$ python main.py

Code Result:

Dependencies

  • OpenCV 3.4.8
  • NumPy
  • Matplotlib

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Research paper Implementation: Natural-based underwater image color enhancement through fusion of swarm-intelligence algorithm

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