The main objective of the Project is to reduce the noises in the Underwater Images. We propose some methods for efficient removal of Noises using Image Processing Techniques. The Underwater images have low quality which makes it a difficult process to analyze the images. Here we propose Image Enhancement and Image Restoration process for increasing the quality of Underwater Images. Clahe, Reyleigh distribution, DCP and MIP,RGHS,ULAP methods are used in this project.
- CLAHE - CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION
- RAYLEIGH DISTRIBUTION
- RGHS - Relative Global Histogram Stretching
- DCP - DARK CHANNEL PRIOR
- MIP - MAXIMUM INTENSITY PROJECTION
- ULAP - Underwater Light Attenuation Prior
- python 3.8.6 64bit
- install dependencies
$ pip install -r requirements.txt
- download models from here, place it in models folder
/UWIE/CLASSIFY/models/
- Pocillopora
- Acropora
- Turf
$ py manage.py runserver
Demo project hosted on heroku link