An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN) of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR) Imagery

An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN) of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR) Imagery

Thermal Infrared (TIR) remote sensing images of urban environments are increasingly available from airborne and satellite platforms. However, limited access to high-spatial resolution (H-res: ~1 m) TIR satellite images requires the use of TIR airborne sensors for mapping large complex urban surfaces...

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Bibliographic Details
Main Authors: Mir Mustafizur Rahman, Geoffrey J. Hay, Isabelle Couloigner, Bharanidharan Hemachandran, Jeremy Bailin
Format: Article
Language:English
Published: MDPI AG 2014-11-01
Series:Remote Sensing
Subjects:
thermal infrared
relative radiometric normalization
non-linear
TABI-1800
no-change stratified random sample
Online Access:http://www.mdpi.com/2072-4292/6/12/11810

Internet

http://www.mdpi.com/2072-4292/6/12/11810

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