  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.
