@article{fdi:010073004,
  title = {{U}nsupervised quantification of under- and over-segmentation for object-based remote sensing image analysis},
  author = {{T}roya-{G}alvis, {A}. and {G}an{\c{c}}arski, {P}. and {P}assat, {N}. and {B}erti-{E}quille, {L}aure},
  editor = {},
  language = {{ENG}},
  abstract = {{O}bject-based image analysis ({OBIA}) has been widely adopted as a common paradigm to deal with very high-resolution remote sensing images. {N}evertheless, {OBIA} methods strongly depend on the results of image segmentation. {M}any segmentation quality metrics have been proposed. {S}upervised metrics give accurate quality estimation but require a ground-truth segmentation as reference. {U}nsupervised metrics only make use of intrinsic image and segment properties; yet most of them strongly depend on the application and do not deal well with the variability of objects in remote sensing images. {F}urthermore, the few metrics developed in a remote sensing context mainly focus on global evaluation. {I}n this paper, we propose a novel unsupervised metric, which evaluates local quality (per segment) by analyzing segment neighborhood, thus quantifying under- and over-segmentation given a certain homogeneity criterion. {A}dditionally, we propose two variants of this metric, for estimating global quality of remote sensing image segmentation by the aggregation of local quality scores. {F}inally, we analyze the behavior of the proposed metrics and validate their applicability for finding segmentation results having good tradeoff between both kinds of errors.},
  keywords = {{ANALYSE} {D}'{IMAGE} ; {TRAITEMENT} {D}'{IMAGE} ; {QUALITE} {D}'{IMAGE} ; {MESURE} ; {SEGMENTATTION} ; {METHODE} {ORIENTEE} {OBJET}},
  booktitle = {},
  journal = {{IEEE} {J}ournal of {S}elected {T}opics in {A}pplied {E}arth {O}bservations and {R}emote {S}ensing},
  volume = {8},
  numero = {5},
  pages = {1936--1945},
  ISSN = {1939-1404},
  year = {2015},
  DOI = {10.1109/{JSTARS}.2015.2424457},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073004},
}