Spline-Based Dense Medial Descriptors for Lossy Image Compression

Jieying Wang, Jiří Kosinka, Alexandru Telea

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Medial descriptors are of significant interest for image simplification, representation, manipulation, and compression. On the other hand, B-splines are well-known tools for specifying smooth curves in computer graphics and geometric design. In this paper, we integrate the two by modeling medial descriptors with stable and accurate B-splines for image compression. Representing medial descriptors with B-splines can not only greatly improve compression but is also an effective vector representation of raster images. A comprehensive evaluation shows that our Spline-based Dense Medial Descriptors (SDMD) method achieves much higher compression ratios at similar or even better quality to the well-known JPEG technique. We illustrate our approach with applications in generating super-resolution images and salient feature preserving image compression.

Original languageEnglish
Article number153
Pages (from-to)1-26
JournalJournal of Imaging
Volume7
Issue number8
DOIs
Publication statusPublished - 19 Aug 2021

Bibliographical note

Funding Information:
Funding: The first author acknowledges the China Scholarship Council (grant number 201806320354) for financial support.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • B-splines
  • Image compression
  • Medial descriptors
  • Super-resolution

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