Image compression with Stochastic Winner-Take-All Auto-Encoder
Thierry Dumas, Aline Roumy, Christine Guillemot
Abstract
This paper addresses the problem of image compression using sparse representations. We propose a variant of autoencoder called Stochastic Winner-Take-All Auto-Encoder (SWTA AE). “Winner-Take-All” means that image patches compete with one another when computing their sparse representation and “Stochastic” indicates that a stochastic hyperparameter rules this competition during training. Unlike auto-encoders, SWTA AE performs variable rate image compression for images of any size after a single training, which is fundamental for compression. For comparison, we also propose a variant of Orthogonal Matching Pursuit (OMP) called Winner-Take-All Orthogonal Matching Pursuit (WTA OMP). In terms of rate-distortion trade-off, SWTA AE outperforms auto-encoders but it is worse than WTA OMP. Besides, SWTA AE can compete with JPEG in terms of rate-distortion.
BibTeX
@inproceedings{icassp2017_imagecompression,
title = {Image compression with Stochastic Winner-Take-All Auto-Encoder},
author = {Thierry Dumas and Aline Roumy and Christine Guillemot},
booktitle = {ICASSP 2017},
year = {2017}
}