GP-grid image interpolation and denoising for division of focal plane sensors

Elad Gilboa, John P. Cunningham, Arye Nehorai, Viktor Gruev

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

Abstract

Image interpolation and denoising are important techniques in image processing. Recently, there has been a growing interest in the use of Gaussian processes (GP) regression for interpolation and denoising of image data. However, exact GP regression suffers from 0 (N3) runtime for data size N, making it intractable for image data. Our GP-grid algorithm reduces the runtime complexity of GP from 0 (N3) to 0 (N31 2). We provide comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter. The GP interpolation method outperforms the commonly used bilinear interpolation method for polarimeters.

Original languageEnglish (US)
Title of host publicationPolarization
Subtitle of host publicationMeasurement, Analysis, and Remote Sensing XI
PublisherSPIE
ISBN (Print)9781628410365
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
EventPolarization: Measurement, Analysis, and Remote Sensing XI - Baltimore, MD, United States
Duration: May 5 2014May 6 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9099
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherPolarization: Measurement, Analysis, and Remote Sensing XI
CountryUnited States
CityBaltimore, MD
Period5/5/145/6/14

Keywords

  • Denoising
  • Gaussian processes
  • Interpolation
  • Polarization devices

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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