adityashrm21 / image-compression-techniques

Image compression using DP, Integer Linear Programming and K-means clustering

Image Compression

Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic compression methods. Here is my blog post where I explain the techniques used along with some code snippets.

Techniques used

This repository contains code for image compression using:

1. Dynamic Programming
2. Integer Linear Programming
3. K-means clustering

Future work

Use Deep Learning (RNNs) for compressing images particularly, the implementation of this paper by Google:

George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell, Full Resolution Image Compression with Recurrent Neural Networks, July 2017