Topological challenges in multispectral image segmentation

Retos topológicos en la segmentación de imágenes multiespectrales

  • José Antonio Valero Medina Universidad Distrital Francisco José de Caldas
  • Iván Alberto Lizarazo Salcedo Universidad Distrital Francisco José de Caldas
  • Paul Elsner University of London
Palabras clave: multispectral images, segmentation, topologic space. (en_US)
Palabras clave: multispectral images, segmentation, topologic space. (es_ES)

Resumen (en_US)

Land cover classification from remote sensing multispectral images has been traditionallyconducted by using mainly spectral information associated with discrete spatial units (i.e. pixels).Geometric and topological characteristics of the spatial context close to every pixel have been either not fully treated or completely ignored.This article provides a review of the strategies used by a number of researchers in order to include spatial and topological properties in image segmentation.­­­It is shown how most of researchers have proposed to perform -previous to classification- a grouping or segmentation of nearby pixels by modeling neighborhood relationships as 4-connected, 8-connected and (a, b) – connected graphs.In this object-oriented approach, however, topological concepts such as neighborhood, contiguity, connectivity and boundary suffer from ambiguity since image elements (pixels) are two-dimensional entities composing a spatially uniform grid cell (i.e. there are not uni-dimensional nor zero-dimensional elements to build boundaries). In order to solve such topological paradoxes, a few proposals have been proposed. This review discusses how the alternative of digital images representation based on Cartesian complexes suggested by Kovalevsky (2008) for image segmentation in computer vision, does not present topological flaws, typical of conventional solutions based on grid cells. However, such a proposal has not been yet applied to multispectral image segmentation in remote sensing.  This review is part of the PhD in Engineering research conducted by the first author under guidance of the second one. This review concludes suggesting the need to research on the potential of using Cartesian complexes for multispectral image segmentation.

Resumen (es_ES)

La clasificación de la cobertura terrestre a partir de imágenes multiespectrales de teledetección se ha llevado a cabo tradicionalmente utilizando información principalmente espectral asociada a unidades espaciales discretas (es decir, píxeles). Las características geométricas y topológicas del contexto espacial cercanas a cada píxel no se han tratado del todo o se han ignorado por completo. proporciona una revisión de las estrategias utilizadas por un número de investigadores para incluir propiedades espaciales y topológicas en la segmentación de imágenes. Se muestra cómo la mayoría de los investigadores han propuesto realizar, antes de la clasificación, una agrupación o segmentación de píxeles cercanos modelando el vecindario relaciones como 4 conectadas, 8 conectadas y (a, b) conectadas. Sin embargo, en este enfoque orientado a objetos, los conceptos topológicos como vecindad, contigüidad, conectividad y límite sufren de ambigüedad ya que los elementos de imagen (píxeles) son dos entidades tridimensionales que componen una celda de cuadrícula espacialmente uniforme (es decir, no hay uni-di elementos mensionales o de cero dimensiones para construir límites). Para resolver tales paradojas topológicas, se han propuesto algunas propuestas. Esta revisión discute cómo la alternativa de representación de imágenes digitales basada en complejos cartesianos sugerida por Kovalevsky (2008) para la segmentación de imágenes en visión artificial, no presenta fallas topológicas, típicas de soluciones convencionales basadas en celdas de grillas. Sin embargo, tal propuesta aún no se ha aplicado a la segmentación de imágenes multiespectrales en teledetección. Esta revisión es parte del doctorado en investigación de ingeniería conducida por el primer autor bajo la dirección del segundo. Esta revisión concluye sugiriendo la necesidad de investigar sobre el potencial del uso de complejos cartesianos para la segmentación de imágenes multiespectrales.

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Biografía del autor/a

José Antonio Valero Medina, Universidad Distrital Francisco José de Caldas

Systems Engineer, master in Teleinformatics, PhD student in engineering. Associate Professor of the Universidad Distrital Francisco José de Caldas. Bogotá. 

Iván Alberto Lizarazo Salcedo, Universidad Distrital Francisco José de Caldas

Civil Engineer, PhD in Geography. Titular Professor of the Universidad Distrital Francisco José de Caldas. Bogotá. 

Paul Elsner, University of London

Physical Geographer. PhD in Geography. Lecturer in Geographical Information Science and Physical Geography, University of London. London, United Kingdom.

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Cómo citar
Valero Medina, J. A., Lizarazo Salcedo, I. A., & Elsner, P. (2014). Retos topológicos en la segmentación de imágenes multiespectrales. Tecnura, 18, 136-149. https://doi.org/10.14483/22487638.9250
Publicado: 2014-12-01