Digital Halftoning with Space Filling Curves

This is an implementation of the digital halftoning technique introduced in the paper "Digital Halftoning with Space-Filling Curves" by Luiz Velho and Jonas de Miranda Gomes. The authors introduced a technique for generating halftone images from grayscale images using space-filling curves. This method is an alternative to the traditional artistic technique of stippling, where varying the density of small dots creates the illusion of continuous tones in an image.

Pre-requisites

This implementation has been written and tested on Ubuntu 22.04.5 LTS using the following packages:

• OpenCV 4.5
• NumPy 1.26.4
• Matplotlib 3.5.1

Usage

 usage: digital_halftoning.py [-h] [-i image_in] [-o image_out] [-t curve_type] [-s cluster_size]
                              [-d distribution] [-g gamma] [-b blur] [-w weight]

 options:
   -h, --help                                    show this help message and exit
   -i image_in, --image_in image_in              path to the input image
   -o image_out, --image_out image_out           path to the output image
   -t curve_type, --curve_type curve_type        type of space filling curve
   -s cluster_size, --cluster_size cluster_size  size of the cluster for halftoning
   -d distribution, --distribution distribution  within-cluster intensity distribution
   -g gamma, --gamma gamma                       gamma value for gamma correction
   -b blur, --blur blur                          blur value for edge enhancement
   -w weight, --weight weight                    weight value for edge enhancement