1 Citation (Scopus)

Abstract

Interpolation is an essential and broadly employed function of signal processing. Accordingly, considerable development has focused on advancing interpolation algorithms toward optimal accuracy. Such development has motivated a clear shift in the state-of-the art from classical interpolation to more intelligent and resourceful approaches, registration-based interpolation for example. As a natural result, many of the most accurate current algorithms are highly complex, specific, and computationally demanding. However, the diverse hardware destinations for interpolation algorithms present unique constraints that often preclude use of the most accurate available options. For example, while computationally demanding interpolators may be suitable for highly equipped image processing platforms (e.g., computer workstations and clusters), only more efficient interpolators may be practical for less well equipped platforms (e.g., smartphones and tablet computers). The latter examples of consumer electronics present a design tradeoff in this regard: high accuracy interpolation benefits the consumer experience but computing capabilities are limited. It follows that interpolators with favorable combinations of accuracy and efficiency are of great practical value to the consumer electronics industry. We address multidimensional interpolation-based image processing problems that are common to consumer electronic devices through a decomposition approach. The multidimensional problems are first broken down into multiple, independent, onedimensional (1-D) interpolation steps that are then executed with a newlymodified registration-based one-dimensional control grid interpolator. The proposed approach, decomposed multidimensional control grid interpolation (DMCGI), combines the accuracy of registrationbased interpolation with the simplicity, flexibility, and computational efficiency of a 1-D interpolation framework. Results demonstrate that DMCGI provides improved interpolation accuracy (and other benefits) in image resizing, color sample demosaicing, and video deinterlacing applications, at a computational cost that is manageable or reduced in comparison to popular alternatives.

Original languageEnglish (US)
Article number43012
JournalJournal of Electronic Imaging
Volume21
Issue number4
DOIs
StatePublished - 2012

Fingerprint

Consumer electronics
interpolation
image processing
Interpolation
Image processing
grids
electronics
repeaters
platforms
tablets
Computer workstations
Electronics industry
Smartphones
workstations
tradeoffs
Computational efficiency
Computer hardware
signal processing
Signal processing
flexibility

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Atomic and Molecular Physics, and Optics

Cite this

Decomposed multidimensional control grid interpolation for common consumer electronic image processing applications. / Zwart, Christine M.; Venkatesan, Ragav; Frakes, David.

In: Journal of Electronic Imaging, Vol. 21, No. 4, 43012, 2012.

Research output: Contribution to journalArticle

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