Image interpolation using multiscale geometric representations

Nickolaus Mueller, Yue Lu, Minh N. Do

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the ever increasing computational power of modern day processors, it has become feasible to use more robust and computationally complex algorithms that increase the resolution of images without distorting edges and contours. We present a novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images. By using a simple wavelet-based linear interpolation scheme as our initial estimate, we use an iterative projection process based on two constraints to drive our solution towards an improved high-resolution image. Our experimental results show that our new algorithm significantly outperforms linear interpolation in subjective quality, and in most cases, in terms of PSNR as well.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging V
DOIs
StatePublished - Aug 31 2007
EventComputational Imaging V - San Jose, CA, United States
Duration: Jan 29 2007Jan 31 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6498
ISSN (Print)0277-786X

Other

OtherComputational Imaging V
CountryUnited States
CitySan Jose, CA
Period1/29/071/31/07

Keywords

  • Contourlet transform
  • Directional multiresolution image representation
  • Geometric regularity
  • Image interpolation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'Image interpolation using multiscale geometric representations'. Together they form a unique fingerprint.

Cite this