Next Article in Journal
Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada
Next Article in Special Issue
Morphological Principal Component Analysis for Hyperspectral Image Analysis
Previous Article in Journal
Amateur or Professional: Assessing the Expertise of Major Contributors in OpenStreetMap Based on Contributing Behaviors
Previous Article in Special Issue
Segmentation of Façades from Urban 3D Point Clouds Using Geometrical and Morphological Attribute-Based Operators
Article Menu

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2016, 5(3), 22; doi:10.3390/ijgi5030022

An Efficient Parallel Algorithm for Multi-Scale Analysis of Connected Components in Gigapixel Images

1
Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, Groningen 9700 AK, The Netherlands
2
Global Security And Crisis Management Unit, Institute for the Protection and Security of the Citizen, Joint Research Centre, European Commission, via Enrico Fermi 2749, Ispra (VA) I-21027, Italy
3
DigitalGlobe, Inc., 1300 W 120th Ave, Westminster, CO 80234, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Beatriz Marcotegui and Wolfgang Kainz
Received: 16 December 2015 / Revised: 28 January 2016 / Accepted: 3 February 2016 / Published: 25 February 2016
(This article belongs to the Special Issue Mathematical Morphology in Geoinformatics)
View Full-Text   |   Download PDF [18380 KB, uploaded 25 February 2016]   |  

Abstract

Differential Morphological Profiles (DMPs) and their generalized Differential Attribute Profiles (DAPs) are spatial signatures used in the classification of earth observation data. The Characteristic-Salience-Leveling (CSL) is a model allowing the compression and storage of the multi-scale information contained in the DMPs and DAPs into raster data layers, used for further analytic purposes. Computing DMPs or DAPs is often constrained by the size of the input data and scene complexity. Addressing very high resolution remote sensing gigascale images, this paper presents a new concurrent algorithm based on the Max-Tree structure that allows the efficient computation of CSL. The algorithm extends the “one-pass” method for computation of DAPs, and delivers an attribute zone segmentation of the underlying trees. The DAP vector field and the set of multi-scale characteristics are computed separately and in a similar fashion to concurrent attribute filters. Experiments on test images of 3.48 to 3.96 Gpixel showed an average computational speed of 59.85 Mpixel per second, or 3.59 Gpixel per minute on a single 2U rack server with 64 opteron cores. The new algorithms could be extended to morphological keypoint detectors capable of handling gigascale images. View Full-Text
Keywords: differential attribute profile; connected filters; spatial signature; CSL model; image decomposition; giga-pixel images differential attribute profile; connected filters; spatial signature; CSL model; image decomposition; giga-pixel images
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wilkinson, M.H.; Pesaresi, M.; Ouzounis, G.K. An Efficient Parallel Algorithm for Multi-Scale Analysis of Connected Components in Gigapixel Images. ISPRS Int. J. Geo-Inf. 2016, 5, 22.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top