Comparing statistical and spatial characteristics of urban and rural infrared images, part 1: Data analysis

Eitan Hirsch, Eyal Agassi, Norman S. Kopeika

Research output: Contribution to journalArticlepeer-review

Abstract

Machine vision of specific objects on natural backgrounds in the IR is an extensively studied subject. Characterizing the clutter is essential in order to evaluate a sensor's performance under various conditions. The Ben-Yosef model is the main one used for the characterization and parameterization of rural background IR images in terms of image statistics and texture. However, to the best of our knowledge, no such parameterization of urban images has been established. The aim of this work is a comparison between statistical and spatial characteristics of urban and rural scenes in the IR and their diurnal dynamics. We conclude that the Ben-Yosef model cannot fully describe the urban scene characteristics, mainly due to the model assumptions regarding the uniform spatial structure of the emissivity and of the magnitude of the solar flux over the scene. Experimental results show that, although daytime urban scenes have high variance in the IR, they have a less complex spatial structure than nighttime images, which are characterized by much lower variance.

Original languageEnglish
Article number046401
Pages (from-to)1-8
JournalOptical Engineering
Volume47
Issue number4
DOIs
StatePublished - 6 May 2008

Keywords

  • Background characterization
  • Clutter
  • Thermal images
  • Urban scene

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