Image Compression with Stochastic Winner-Take-All Auto-Encoder

Thierry Dumas (1) , Aline Roumy (1) , Christine Guillemot (1)

1 Sirocco - Analysis representation, compression and communication of visual data

This paper addresses the problem of image compression using sparse representations. We propose a variant of auto-encoder 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 out-performs auto-encoders but it is worse than WTA OMP. Besides , SWTA AE can compete with JPEG in terms of rate-distortion.

Mots clés: Image compression; Sparse representations; Auto-encoders; Orthogonal Matching Pursuit

Domaines: Traitement des images [eess.IV]; Apprentissage [cs.LG]

Thierry Dumas, Aline Roumy, Christine Guillemot. Image Compression with Stochastic Winner-Take-All Auto-Encoder. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. ⟨hal-01493137⟩