Canny Edge Detection in Cross-Spectral Fused Images

Authors

  • Patricia Suárez Escuela Superior Politécnica del Litoral
  • Mónica Villavicencio Escuela Superior Politécnica del Litoral

DOI:

https://doi.org/10.29019/enfoqueute.v8n1.127

Keywords:

Structuring elements, morphological filter, GQM, near infrared, fusion, cross-spectral images

Abstract

Considering that the images of different spectra provide an ample information that helps a lo in the process of identification and distinction of objects that have unique spectral signatures. In this paper, the use of cross-spectral images in the process of edge detection is evaluated. This study aims to assess the Canny edge detector with two variants. The first relates to the use of merged cross-spectral images and the second the inclusion of morphological filters. To ensure the quality of the data used in this study the GQM (Goal-Question- Metrics), framework, was applied to reduce noise and increase the entropy on images. The metrics obtained in the experiments confirm that the quantity and quality of the detected edges increases significantly after the inclusion of a morphological filter and a channel of near infrared spectrum in the merged images.

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Published

2017-02-24

How to Cite

Suárez, P., & Villavicencio, M. (2017). Canny Edge Detection in Cross-Spectral Fused Images. Enfoque UTE, 8(1), pp. 16 – 30. https://doi.org/10.29019/enfoqueute.v8n1.127

Issue

Vol. 8 No. 1 (2017): INCISCOS 2016, Special Edition

Section

Miscellaneous

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