We present the enrichment of the Prague Texture Segmentation Data-Generator and Benchmark (PTSDB) to include the assessment of the remote sensing (RS) image segmenters. The PTSDB tool is a Web-based (http://mosaic.utia.cas.cz) service designed for real-time performance evaluation, mutual comparison, and ranking of various supervised or unsupervised static or dynamic image segmenters. PTSDB supports rapid verification and development of new segmentation approaches. The RS datasets contain ten spectral Advanced Land Imager (ALI) satellite images, their RGB subsets, and very-high-resolution GeoEye RGB images, with optional additive-noise-resistance checking. Alternative setting options allow us to also test scale, rotation, or illumination invariance. The meaningfulness of the newly proposed dataset is demonstrated by testing and comparing several RS segmentation algorithms, and showing that the benchmark figures provide a solid framework for the fair and critical comparison among different techniques.

Benchmarking of Remote Sensing Segmentation Methods / Mikes, Stanislav; Haindl, Michal; Scarpa, Giuseppe; Gaetano, Raffaele. - In: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. - ISSN 1939-1404. - 8:5(2015), pp. 2240-2248. [10.1109/JSTARS.2015.2416656]

Benchmarking of Remote Sensing Segmentation Methods

SCARPA, GIUSEPPE;GAETANO, RAFFAELE
2015

Abstract

We present the enrichment of the Prague Texture Segmentation Data-Generator and Benchmark (PTSDB) to include the assessment of the remote sensing (RS) image segmenters. The PTSDB tool is a Web-based (http://mosaic.utia.cas.cz) service designed for real-time performance evaluation, mutual comparison, and ranking of various supervised or unsupervised static or dynamic image segmenters. PTSDB supports rapid verification and development of new segmentation approaches. The RS datasets contain ten spectral Advanced Land Imager (ALI) satellite images, their RGB subsets, and very-high-resolution GeoEye RGB images, with optional additive-noise-resistance checking. Alternative setting options allow us to also test scale, rotation, or illumination invariance. The meaningfulness of the newly proposed dataset is demonstrated by testing and comparing several RS segmentation algorithms, and showing that the benchmark figures provide a solid framework for the fair and critical comparison among different techniques.
2015
Benchmarking of Remote Sensing Segmentation Methods / Mikes, Stanislav; Haindl, Michal; Scarpa, Giuseppe; Gaetano, Raffaele. - In: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. - ISSN 1939-1404. - 8:5(2015), pp. 2240-2248. [10.1109/JSTARS.2015.2416656]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/612870
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