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- Title
Contrast Invariant SNR and Isotonic Regressions.
- Authors
Weiss, Pierre; Escande, Paul; Bathie, Gabriel; Dong, Yiqiu
- Abstract
We design an image quality measure independent of contrast changes, which are defined as a set of transformations preserving an order between the level lines of an image. This problem can be expressed as an isotonic regression problem. Depending on the definition of a level line, the partial order between adjacent regions can be defined through chains, polytrees or directed acyclic graphs. We provide a few analytic properties of the minimizers and design original optimization procedures together with a full complexity analysis. The methods worst case complexities range from O(n) for chains, to O (n log n) for polytrees and O (n 2 ϵ) for directed acyclic graphs, where n is the number of pixels and ϵ is a relative precision. The proposed algorithms have potential applications in change detection, stereo-vision, image registration, color image processing or image fusion. A C++ implementation with Matlab headers is available at https://github.com/pierre-weiss/contrast_invariant_snr.
- Subjects
ISOTONIC regression; COLOR image processing; DIRECTED acyclic graphs; IMAGE fusion; IMAGE processing; IMAGE registration
- Publication
International Journal of Computer Vision, 2019, Vol 127, Issue 8, p1144
- ISSN
0920-5691
- Publication type
Article
- DOI
10.1007/s11263-019-01161-9