Contrast Invariant SNR

Pierre Weiss, Paul Escande, Yiqiu Dong

Research output: Book/ReportReportResearch

101 Downloads (Pure)

Abstract

We design an image quality measure independent of local contrast changes, which constitute simple models of illumination changes. Given two images, the algorithm provides the image closest to the first one with the component tree of the second. This problem can be cast as a specific convex program called isotonic regression. We provide a few analytic properties of the solutions to this problem. We also design a tailored first order optimization procedure together with a full complexity analysis. The proposed method turns out to be practically more efficient and reliable than the best existing algorithms based on interior point methods. The algorithm has potential applications in change detection, color image processing or image fusion. A Matlab implementation is available at http://www.math.univ-toulouse.fr/_weiss/PageCodes.html.
Original languageEnglish
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Number of pages8
Publication statusPublished - 2016
SeriesDTU Compute-Technical Report-2016
Number9
ISSN1601-2321

Keywords

  • Local contrast change
  • Topographic map
  • Isotonic regression
  • Convex optimization
  • Illumination invariance
  • Signal-to-noise-ratio
  • Image quality measure

Cite this

Weiss, P., Escande, P., & Dong, Y. (2016). Contrast Invariant SNR. Technical University of Denmark. DTU Compute-Technical Report-2016, No. 9