[](https://zenodo.org/badge/latestdoi/261705729)

This repository contains C++ and Python 3 implementation of an image smoothing algorithm that was proposed in this [publication](https://ieeexplore.ieee.org/document/9117646).


Requirements for C++:

- opencv 4.3.0 if you want Mat type support

- opencv 4.3.0 if you want Mat type support

Here is the simple example of filter usage with opencv Mat images:

return 0;

}

Python requirements are in file requirements.txt

use:

`pip install --upgrade pip`

`pip install -r requirements.txt`

Here is example with python:

import filter_based_on_gradient_analysis as fga

import cv2

Our algorithm uses filtering and to achieve edge-preserving smoothing it uses two components of gradient vectors: their magnitudes (or lengths) and directions. Our method discriminates between two types of boundaries in given neighborhood: regular and irregular ones.


Regular boundaries have small deviations of gradient angles and the opposite for irregular ones. To measure closeness of angles cosine of doubled difference is used. As additional measure that helps to discriminate the types of boundaries inverted gradient values were used.

If you used the code or want to reference this method in your work, please cite: