Gauss filtration-based feature extraction for IR images analysis

Lixin Wu, Shanjun Liu, Yongqiang Li, Wenzhong Shi, Yuhua Wu

Research output: Journal article publicationConference articleAcademic researchpeer-review


Infrared (IR) image analysis is important for extracting IR anomaly features in the fundamental experiments of Remote Sensing Rock Mechanics (RSRM) and for identifying omen for tectonic earthquake based on satellite remote sensing monitoring. Transferring the IR image into a raster contour map is very useful, but usually a raster contour map transferred is not smooth enough for the disturbance of noise and the limitation of spatial resolution of the image. A Gauss filter, G(i, j) = kei2+j2/σ2, is selected for generating raster contour map. The practical application cases in image analysis and feature extraction for RSRM experiments suggest that the raster contour map is smooth enough for quantitative analysis, and is helpful for IR feature extraction and for anomaly identification. As compared to mean filter and median filter, the Gauss filter is effective both in filtering speed and in contour map's quality for the condition that filter width be 9-15 and σ be 0.2-0.6.

Original languageEnglish
Pages (from-to)496-503
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2004
EventImage and Signal Processing for Remote Sensing IX - Barcelona, Spain
Duration: 9 Sep 200312 Sep 2003


  • Features extraction
  • Gauss filter
  • Infrared image
  • Quality
  • Raster contour map
  • Remote sensing rock mechanics (RSRM)
  • Signal-to-mask ratio
  • Smooth

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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