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Template Matching with Noisy Patches: A Contrast-Invariant GLR Test

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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Contributor : Charles-Alban Deledalle <>
Submitted on : Monday, March 25, 2013 - 3:51:21 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:58 PM
Document(s) archivé(s) le : Wednesday, June 26, 2013 - 4:03:12 AM


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  • HAL Id : hal-00804483, version 1
  • ARXIV : 1303.6152


Charles-Alban Deledalle, Loïc Denis, Florence Tupin. Template Matching with Noisy Patches: A Contrast-Invariant GLR Test. European Signal Processing Conference 2013, Sep 2013, Marrakech, Morocco. ⟨hal-00804483⟩



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