Morphological reconstruction algorithms for urban monitoring using satellite data: proper selection of the marker and mask images

ABSTRACT

Morphological processing has found several applications in image analysis and pattern recognition. Some of these techniques, known as morphological reconstruction algorithms, have been employed for land cover classification in remote sensing data. In this paper, we analyse the mathematical foundations, applications, and limitations of reconstruction by dilation and by erosion oriented to urban extraction, using Sentinel-2 satellite data. Different techniques oriented to the proper determination of the marker and mask images, the basis for reconstruction, are proposed in this manuscript. In addition, in order to diminish the long computation time required for reconstruction, two parallel implementations using Multi-core and GPU, are proposed. According to our research, these algorithms can be considered as effective and non-supervised solutions for urban extraction applications based on multispectral satellite imagery.

Disclosure statement

The authors declare no conflict of interest regarding the publication of this manuscript.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

Authors would like to thank the support from “Laboratorio de Supercómputo del Bajío” through CONACyT Grant Number 300832.