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Publications sur topographic map
Résultat de la recherche dans la liste des publications :
Article |
1 - On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection.
P. Weiss et A. Fournier et L. Blanc-Féraud et G. Aubert. SIAM Journal on Imaging Sciences, 4(1): pages 448-471, mars 2011.
Mots-clés : Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing.
@ARTICLE{SIIMS_2011,
|
| author |
= |
{Weiss, P. and Fournier, A. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection}, |
| year |
= |
{2011}, |
| month |
= |
{mars}, |
| journal |
= |
{SIAM Journal on Imaging Sciences}, |
| volume |
= |
{4}, |
| number |
= |
{1}, |
| pages |
= |
{448-471}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, |
| keyword |
= |
{Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing} |
| } |
Abstract :
We analyze the illumination invariance of the level lines of an image. We show that if the scene
surface has Lambertian reflectance and the light is directed, then a necessary and sufficient condition
for the level lines to be illumination invariant is that the three-dimensional scene be developable and
that its albedo satisfy some geometrical constraints. We then show that the level lines are “almost”
invariant for piecewise developable surfaces. Such surfaces fit most of the urban structures. This
allows us to devise a fast and simple algorithm that detects changes between pairs of remotely
sensed images of urban areas, independently of the lighting conditions. We show the effectiveness of
the algorithm both on synthetic OpenGL scenes and real QuickBird images. The synthetic results
illustrate the theory developed in this paper. The two real QuickBird images show that the proposed
change detection algorithm is discriminant. For easy scenes it achieves a rate of 85% detected changes
for 10% false positives, while it reaches a rate of 75% detected changes for 25% false positives on
demanding scenes.
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