Abstract
Feature extraction, noise removal
Naoki Saito
University of California, Davis (UC Davis)
Tutorial I: Feature Extraction and Denoising: A Saga of U+V Models
I will review the so-called U+V models in image representation and denoising context. Under these models, the original data f is assumed to
consist of the u component that captures the main important "features", and the v component that are mainly textures and noise. Going over the various models, such as Mumford-Shah, Rudin-Osher-Fatemi, DeVore-Lucier, Chen-Donoho-Saunders, Cohen-Daubechies-Dahmen-DeVore, etc., I will discuss how the U component are modeled mathematically, and how much they reflect the reality. I will also discuss the recent interactions between harmonic analysis and PDE for image processing.
This tutorial should naturally leads to the lectures of Donoho and Candes on Friday.
I will review the so-called U+V models in image representation and denoising context. Under these models, the original data f is assumed to
consist of the u component that captures the main important "features", and the v component that are mainly textures and noise. Going over the various models, such as Mumford-Shah, Rudin-Osher-Fatemi, DeVore-Lucier, Chen-Donoho-Saunders, Cohen-Daubechies-Dahmen-DeVore, etc., I will discuss how the U component are modeled mathematically, and how much they reflect the reality. I will also discuss the recent interactions between harmonic analysis and PDE for image processing.
This tutorial should naturally leads to the lectures of Donoho and Candes on Friday.
No video available