Paper
27 April 2000 Standard palettes for GPR data analysis
L. D. Hunt, D. Massie, J. P. Cull
Author Affiliations +
Proceedings Volume 4084, Eighth International Conference on Ground Penetrating Radar; (2000) https://doi.org/10.1117/12.383589
Event: 8th International Conference on Ground Penetrating Radar, 2000, Gold Coast, Australia
Abstract
Most GPR profiles are displayed in point mode form. This gives an amplitude color coded image where waveform amplitudes are plotted according to predefined colors (forming a palette). They are similar in concept to early GPR hard copy products based on gray scale distributions but they provide grater flexibility and dynamic range for anomaly recognition. A wiggle mode trace can also be included as an overlay on the color image to assist with wavelet recognition and enhance lateral correlations. However, more subtle components of the waveform (in particular phase relationships) are often ignored. Many data reduction, image display, and signal processing algorithms used for GPR surveys have been borrowed from remote sensing, seismic and general geophysical exploration techniques. However, they have been implemented in a relatively primitive form. In particular, the advantages of correct and relevant color palette selection for point mode images have been ignored. More rational palettes are now proposed to convey amplitude features, in combination with phase information, for analysis of target properties.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. D. Hunt, D. Massie, and J. P. Cull "Standard palettes for GPR data analysis", Proc. SPIE 4084, Eighth International Conference on Ground Penetrating Radar, (27 April 2000); https://doi.org/10.1117/12.383589
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
General packet radio service

Antennas

Radar

Signal processing

Data analysis

Metals

Visualization

Back to Top