Automatic image segmentation optimized by bilateral filtering

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Abstract

The object-based methodology is one of the most commonly used strategies for processing high spatial resolution images. A prerequisite to object-based image analysis is image segmentation, which is normally defined as the subdivision of an image into separated regions. This study proposes a new image segmentation methodology based on a self-calibrating multi-band region growing approach. Two multispectral aerial images were used in this study. The unsupervised image segmentation approach begins with a first step based on a bidirectional filtering, in order to eliminate noise, smooth the initial image and preserve edges. The results are compared with ones obtained from Definiens Developper software. © 2010 Springer-Verlag.

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Sanchez, J., Martinez, E., Arquero, A., & Renza, D. (2010). Automatic image segmentation optimized by bilateral filtering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6419 LNCS, pp. 303–310). https://doi.org/10.1007/978-3-642-16687-7_42

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