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arXiv · 1303.6152

Template matching with noisy patches: A contrast-invariant GLR test

Charles-Alban Deledalle·Loïc Denis·Florence Tupin
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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.

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Charles-Alban Deledalle, Loïc Denis, Florence Tupin. 2013-03-25. Template matching with noisy patches: A contrast-invariant GLR test. https://arxiv.org/abs/1303.6152

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