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