Texture variable analysis for landscape patches represented using super-resolution mapping

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

Abstract

This paper presents the analyses of texture variables from the image enhanced using super-resolution mapping. Two widely known super-resolution mapping techniques, pixel swapping and Hopfield neural network are used. The texture analyses include land cover patches of varying sizes, shapes, and spatial pattern of patches. A time series coarse MODIS 250 images are used to improve the representation of land cover patches and reduce the spatial variability. Results show that using a fusion of time series images and properly setting the weights for the Hopfield neural network produce superior accuracy of representing the texture of land cover mapping.

Original languageEnglish
Title of host publication2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages51-56
Number of pages6
ISBN (Electronic)9781538603802
DOIs
Publication statusPublished - 17 Oct 2017
Event8th IEEE Control and System Graduate Research Colloquium, ICSGRC 2017 - Shah Alam, Malaysia
Duration: 4 Aug 20175 Aug 2017

Other

Other8th IEEE Control and System Graduate Research Colloquium, ICSGRC 2017
CountryMalaysia
CityShah Alam
Period4/8/175/8/17

Fingerprint

Land Cover
Super-resolution
Patch
Texture
Hopfield neural networks
Hopfield Neural Network
textures
Textures
Time series
Spatial Variability
MODIS
MODIS (radiometry)
Spatial Pattern
Fusion
Fusion reactions
fusion
Pixel
Pixels
pixels

Keywords

  • Hopfield neural network
  • Landscape pattern
  • Pixel swapping
  • Remote sensing
  • Texture variable

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Instrumentation

Cite this

Muad, A. M. (2017). Texture variable analysis for landscape patches represented using super-resolution mapping. In 2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings (pp. 51-56). [8070567] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSGRC.2017.8070567

Texture variable analysis for landscape patches represented using super-resolution mapping. / Muad, Anuar Mikdad.

2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 51-56 8070567.

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

Muad, AM 2017, Texture variable analysis for landscape patches represented using super-resolution mapping. in 2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings., 8070567, Institute of Electrical and Electronics Engineers Inc., pp. 51-56, 8th IEEE Control and System Graduate Research Colloquium, ICSGRC 2017, Shah Alam, Malaysia, 4/8/17. https://doi.org/10.1109/ICSGRC.2017.8070567
Muad AM. Texture variable analysis for landscape patches represented using super-resolution mapping. In 2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 51-56. 8070567 https://doi.org/10.1109/ICSGRC.2017.8070567
Muad, Anuar Mikdad. / Texture variable analysis for landscape patches represented using super-resolution mapping. 2017 IEEE 8th Control and System Graduate Research Colloquium, ICSGRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 51-56
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