A total variation denoising implementation in python.
Project description
This is a Python implementation of Total Variation Denoising method proposed by Guy Gilboa.
Reduces the total-variation of the image. Filters out noise while preserving edges. Textures and fine-scale details are also removed.
Requirements
To run this code you need the following packages:
Everything but OpenCV can be installed via ``pip install -r requirements``
Installation
To install everything just type:
pip install py-tvd
For manual installation:
python setup.py install
Probably you have to run it with sudo.
Testing
Test are provided via unittest.
To run them all:
nosetests
Examples
import cv2
from tvd import TotalVariationDenoising
import os
image = cv2.imread(os.path.dirname(__file__) + '/../assets/example.bmp')
image = cv2.cvtColor(image, cv2.COLOR_BGR2YCR_CB)
subject = TotalVariationDenoising(image[:, :, 0])
output = subject.generate()
cv2.imshow('Total Variation Denoising image', output / 255)
cv2.waitKey(0)
cv2.destroyAllWindows()
The conversion to YCbCr color space is optionally (sure?)
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