Keyword Search:

Spatial data compression and denoising via wavelet transformation

Pradhan, Biswajeet and Kumar, Naresh and Mansor, Shattri and Ramli, Abdul Rahman and Mohamed Sharif, Abdul Rashid (2006) Spatial data compression and denoising via wavelet transformation. Applied GIS, 2 (1). 6.1-6.16. ISSN 1832-5505

Full text not available from this repository.

Official URL: http://dx.doi.org/10.2104/ag060006

Abstract

A new interpolation wavelet filter for TIN data compression has been applied in two steps, namely splitting and lifting. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. This data set is then compressed at the desired locations by using second-generation wavelets: scalar wavelets constructed by using a lifting scheme. Application of the compressed data compares favourably with results derived using the original (and much larger) TIN data set.

Item Type:Article
Keyword:Compression; Data set; Elevation; Interpolation; Spatial data; Triangulation; Wavelet
Subject:Data compression (Computer science)
Subject:Wavelets (Mathematics)
Subject:Interpolation
Faculty or Institute:Institute of Advanced Technology
DOI Number:10.2104/ag060006
Altmetrics:http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.2104/ag060006
ID Code:18297
Deposited By: Azwana Abdul Rahman
Deposited On:24 Oct 2011 14:34
Last Modified:24 Oct 2011 14:34

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 24 Oct 2011 14:34.

View statistics for "Spatial data compression and denoising via wavelet transformation"

 
 
 
 

Universiti Putra Malaysia Institutional Repository is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.
Universiti Putra Malaysia Institutional Repository supports OAI 2.0 with a base URL of http://psasir.upm.edu.my/cgi/oai2
Best viewed using IE version 7.0 (and above) Mozilla Firefox version 3 (and above) with the resolution of 1024 x 768.