Data Dialogue
Thursday, April 28, 2016, 11:45am, Gross 330
Hoang Duy Thai
Textured Image Deconvolution and Decomposition
Abstract:
Approximation theory is at the heart of image analysis, especially image deconvolution and decomposition. For piecewise smooth images, there are many methods that have been developed over the past several decades. The goal of this study is to illustrate a difficult issue in texture analysis of images which has forensic applications (e.g. to fingerprinting, ballistic images and shoe prints). In particular, it is known that texture information is almost destroyed by a blur operator, such as results from a ballistic image captured by a low-cost microscope. The contribution of this work is twofold. First, we propose a mathematical model for textured image deconvolution and decomposition into several meaningful components. That deconvolution uses a fourth-order PDE approach based on the directional mean curvature. Second, we discover a link between functional analysis and sampling theory, as in harmonic analysis and filter banks. This is preliminary work for a challenging project in estimation of image quality. It requires extensive pre-processing steps and approximation theory. Joint work with David Banks

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