Multilevel detection method for multispectral and hyperspectral images

Aleksandar Zavaljevski, Atam P. Dhawan, David J. Kelch, James Riddell

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

1 Scopus citations

Abstract

A novel multi-level detection (MLD) method for detecting small targets within multispectral images, that takes into account both spectral and spatial characteristics of the data, is proposed. In the first level of processing, misclassification is minimized by applying minimum distance statistical classifier in conjunction with a spectral library of known class signatures. In a second level, the neighborhood of each unclassified pixel is analyzed for detection of candidate classes for use as endmembers in a spectral unmixing model. The fractions of neighborhood and target signatures for the unclassified pixels are determined by means of linear least-squares method. The third processing level determines the size and location of detected targets with a clustering analysis methodology. Target size and location are estimated on the basis of the sum and weighted vector mean, respectively, of the mixing fractions of the neighboring pixels. The MLD method was successfully applied to both synthetic and AVIRIS hyperspectral imagery data sets.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Pages604-614
Number of pages11
StatePublished - Dec 1 1995
Externally publishedYes
EventSignal Processing, Sensor Fusion, and Target Recognition IV - Orlando, FL, USA
Duration: Apr 17 1995Apr 19 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2484

Other

OtherSignal Processing, Sensor Fusion, and Target Recognition IV
CityOrlando, FL, USA
Period4/17/954/19/95

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All Science Journal Classification (ASJC) codes

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

Cite this

Zavaljevski, A., Dhawan, A. P., Kelch, D. J., & Riddell, J. (1995). Multilevel detection method for multispectral and hyperspectral images. In Proceedings of SPIE - The International Society for Optical Engineering (pp. 604-614). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2484).