Edge-based compression of cartoon-like images with homogeneous diffusion

Markus Mainberger, Andrés Bruhn, Joachim Weickert, Søren Forchhammer

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Edges provide semantically important image features. In this paper a lossy compression method for cartoon-like images is presented, which is based on edge information. Edges together with some adjacent grey/colour values are extracted and encoded using a classical edge detector, binary compression standards such as JBIG and state-of-the-art encoders such as PAQ. When decoding, information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. For the discrete reconstruction problem, we prove existence and uniqueness and establish a maximum–minimum principle. Furthermore, we describe an efficient multigrid algorithm. The result is a simple codec that is able to encode and decode in real time. We show that for cartoon-like images this codec can outperform the JPEG standard and even its more advanced successor JPEG2000.
Original languageEnglish
JournalPattern Recognition
Volume44
Issue number9
Pages (from-to)1859-1873
ISSN0031-3203
DOIs
Publication statusPublished - 2011

Keywords

  • Cartoon-like images
  • Contour coding
  • Partial differentialequations(PDEs)
  • Image compression
  • Second-generation coding
  • Laplace equation
  • Multigrid

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