Products of ``Edge-perts

Images represent an important and abundant source of data. Understanding theirstatistical structure has important applications such as image compression and restoration. In this paper we propose a particular kind of probabilistic model, dubbed the "products of edge-perts model" to describe thestructure of wavelet transformed images. We develop a practical denoising algorithm based on a single edge-pert and show state-ofthe-art denoisingperformance on benchmark images.