Enhancing Signal Discontinuities with Shearlets: An Application to Corner Detection

  • Miguel Alejandro Duval-Poo
  • Francesca OdoneEmail author
  • Ernesto De Vito
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)


Shearlets are a relatively new and very effective multi-resolution framework for signal analysis able to capture efficiently the anisotropic information in multivariate problem classes. For this reason, Shearlets appear to be a valid choice for multi-resolution image processing and feature detection. In this paper we provide a brief review of the theory, referring in particular to the problem of enhancing signal discontinuities. We then discuss the specific application to corner detection, and provide a novel algorithm based on the concept of a cornerness measure. The appropriateness of the algorithm in detecting good matchable corners is evaluated on benchmark data including different image transformations.


Corner Point Corner Detection Multivariate Problem Class Texture Scene Signal Discontinuity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Miguel Alejandro Duval-Poo
    • 1
  • Francesca Odone
    • 1
    Email author
  • Ernesto De Vito
    • 2
  1. 1.DIBRIS - Università Degli Studi di GenovaGenoaItaly
  2. 2.DIMA - Università Degli Studi di GenovaGenoaItaly

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