Template Matching with Noisy Patches: A Contrast-Invariant GLR Test
Language
en
Communication dans un congrès
This item was published in
European Signal Processing Conference 2013, 2013-09-09, Marrakech.
English Abstract
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches that are identical up ...Read more >
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches that are identical up to a radiometric transformation, dictionary size can be kept small, thereby retaining good computational efficiency. Identification of the atom in best match with a given noisy patch then requires a contrast-invariant criterion. In the light of detection theory, we propose a new criterion that ensures contrast invariance and robustness to noise. We discuss its theoretical grounding and assess its performance under Gaussian, gamma and Poisson noises.Read less <
English Keywords
Template matching
Likelihood ratio test
Detection theory
Image restoration
Origin
Hal imported