Template matching with noisy patches: A contrast-invariant GLR test
Applications
2013-03-26 v1
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 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.
Keywords
Cite
@article{arxiv.1303.6152,
title = {Template matching with noisy patches: A contrast-invariant GLR test},
author = {Charles-Alban Deledalle and Loïc Denis and Florence Tupin},
journal= {arXiv preprint arXiv:1303.6152},
year = {2013}
}