%0 Book Section
%A LeQuere, P.
%A Maupin, P.
%A Desjardins, R.
%A Mouchot, M-C
%A St-Onge, B.
%A Solaiman, B.
%T Change detection from remotely sensed multi-temporal images using morphological operators
%B Dig Int Geosci Remote Sens Symp (IGARSS)
%D 1997
%E Anon
%V 1
%P 252--254
%C Ecole Nationale Superieure des, Telecommunications de Bretagne, Brest,
France
%I IEEE
%X This paper presents a new approach to spatial change detection. The
algorithms developed are based on the use of basic morphological
filters and on more advanced concepts such as geodesic transformations.
Such techniques are able to overcome the traditional problems associated
with change detection from remotely sensed multi-temporal images.
As a matter of fact it is already known that traditional methods
using the concept of direction variation of the change vector are
inadequate for a precise detection. These frequential techniques
lay on very limitative statistical hypotheses : gaussian distribution,
a priori determined ratio of change, very large images and relatively
small ratio of change. However in a prior study, it was determined
that the basic operators of mathematical morphology were partly
corrupting the results of change detection by introducing bias on
the shape of the objects and also by shifting the edges in the displacement
direction of the structuring element. The geodesic transformations
are correcting these topological difficulties in an elegant way.
The usual threshold step is replaced by appropriate structuring
element interval of sizes. Thus, it becomes possible to treat the
spatial change detection problem by using a single formalism. The
first results show that the particles of change are detected even
for very slight radiometric variations, with the advantage of taking
into account the configuration of the neighbourhood.
%2 Export Date: 24 August 2007
Source: Scopus
CODEN: IGRSE
Language of Original Document: English
Correspondence Address: Le Quere, Pascal; Ecole Nationale Superieure
des; Telecommunications de Bretagne Brest, France
%K Algorithms, Mathematical morphology, Mathematical operators, Object
recognition, Statistical methods, Vectors, Spatial change detection,
Remote sensing
%# brugerolles
%Z timestamp=(2007.12.05)
%U http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0030691707&partnerID=40&rel=R6.5.0
%F LeQuereMaupinDesjardinsEtAl1997
%3 BibTeX type = INPROCEEDINGS