Montag, 20. April 2015, 11:30 - 12:30 iCal

"The SURE-LET Methodology for Image Denoising"

CS-Colloquium: Prof. Blu

Fakultät für Informatik / SR11
Währinger Straße 29, 1090 Wien


The goal of this presentation is to promote a new approach for dealing with noisy data --- typically, images or videos here. Image denoising consists in approximating the noiseless image by performing some (usually non-linear) processing of the noisy image. Most standard techniques involve prior assumptions on the result of this processing (sparsity, low high-frequency contents, etc.); i.e., on the denoised image. Contrasting with these approaches, the SURE-LET methodology does not require any prior knowledge, apart from the noise statistics (Gaussian). It consists in approximating the processing itself (seen as a function) over a linear combination of elementary non-linear processings (LET: Linear Expansion of Thresholds), and to optimize the coefficients of this combination by minimizing a statistically unbiased estimate of the Mean Square Error (SURE: Stein's Unbiased Risk Estimate, in the case of additive Gaussian noise). We will introduce the technique and outline its advantages (fast, noise-robust, flexible, image adaptive). A comprehensive set of results will be shown and compared with the state-of-the-art.

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Fakultät für Informatik


Werner Schröttner
Fakultät für Informatik