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Computer Optics, 2018, Volume 42, Issue 6, Pages 1008–1014
DOI: https://doi.org/10.18287/2412-6179-2018-42-6-1008-1014
(Mi co586)
 

This article is cited in 6 scientific papers (total in 6 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

On the automation of gestalt perception in remotely sensed data

E. Michaelsen

Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany
References:
Abstract: Gestalt perception, the laws of seeing, and perceptual grouping is rarely addressed in the context of remotely sensed imagery. The paper at hand reviews the corresponding state as well in machine vision as in remote sensing, in particular concerning urban areas. Automatic methods can be separated into three types: 1) knowledge-based inference, which needs machine-readable knowledge, 2) automatic learning methods, which require labeled or un-labeled example images, and 3) perceptual grouping along the lines of the laws of seeing, which should be pre-coded and should work on any kind of imagery, but in particular on urban aerial or satellite data. Perceptual grouping of parts into aggregates is a combinatorial problem. Exhaustive enumeration of all combinations is intractable. The paper at hand presents a constant-false-alarm-rate search rationale. An open problem is the choice of the extraction method for the primitive objects to start with. Here super-pixel-segmentation is used.
Keywords: perceptual grouping, remote sensing, urban areas.
Received: 15.03.2018
Accepted: 20.10.2018
Document Type: Article
Language: English
Citation: E. Michaelsen, “On the automation of gestalt perception in remotely sensed data”, Computer Optics, 42:6 (2018), 1008–1014
Citation in format AMSBIB
\Bibitem{Mic18}
\by E.~Michaelsen
\paper On the automation of gestalt perception in remotely sensed data
\jour Computer Optics
\yr 2018
\vol 42
\issue 6
\pages 1008--1014
\mathnet{http://mi.mathnet.ru/co586}
\crossref{https://doi.org/10.18287/2412-6179-2018-42-6-1008-1014}
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  • https://www.mathnet.ru/eng/co586
  • https://www.mathnet.ru/eng/co/v42/i6/p1008
  • This publication is cited in the following 6 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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