Superpixel-based roughness measure for multispectral satellite image segmentation

Ortiz Toro, César Antonio and Gonzalo Martín, Consuelo and García Pedrero, Ángel Mario and Menasalvas Ruiz, Ernestina (2015). Superpixel-based roughness measure for multispectral satellite image segmentation. "Remote sensing", v. 7 (n. 11); pp. 14620-14645. ISSN 2072-4292. https://doi.org/10.3390/rs71114620.

Description

Title: Superpixel-based roughness measure for multispectral satellite image segmentation
Author/s:
  • Ortiz Toro, César Antonio
  • Gonzalo Martín, Consuelo
  • García Pedrero, Ángel Mario
  • Menasalvas Ruiz, Ernestina
Item Type: Article
Título de Revista/Publicación: Remote sensing
Date: 2015
ISSN: 2072-4292
Volume: 7
Subjects:
Freetext Keywords: Unsupervised segmentation; Histon; Rough-set; Region merging
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The new generation of artificial satellites is providing a huge amount of Earth observation images whose exploitation can report invaluable benefits, both economical and environmental. However, only a small fraction of this data volume has been analyzed, mainly due to the large human resources needed for that task. In this sense, the development of unsupervised methodologies for the analysis of these images is a priority. In this work, a new unsupervised segmentation algorithm for satellite images is proposed. This algorithm is based on the rough-set theory, and it is inspired by a previous segmentation algorithm defined in the RGB color domain. The main contributions of the new algorithm are: (i) extending the original algorithm to four spectral bands; (ii) the concept of the superpixel is used in order to define the neighborhood similarity of a pixel adapted to the local characteristics of each image; (iii) and two new region merged strategies are proposed and evaluated in order to establish the final number of regions in the segmented image. The experimental results show that the proposed approach improves the results provided by the original method when both are applied to satellite images with different spectral and spatial resolutions.

More information

Item ID: 40845
DC Identifier: http://oa.upm.es/40845/
OAI Identifier: oai:oa.upm.es:40845
DOI: 10.3390/rs71114620
Official URL: http://www.mdpi.com/2072-4292/7/11/14620
Deposited by: Memoria Investigacion
Deposited on: 26 Oct 2016 15:21
Last Modified: 26 Oct 2016 15:21
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