A STATISTICAL MODEL OF SEA CLUTTER IN PANCHROMATIC HIGH RESOLUTION IMAGES
| Autor: | Guillaume Jubelin, Ali Khenchaf |
|---|---|
| Přispěvatelé: | Lab-STICC_ENSTAB_MOM_PIM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Billon-Coat, Annick |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
010505 oceanography
Computer science [SPI.ELEC] Engineering Sciences [physics]/Electromagnetism 0211 other engineering and technologies Statistical model 02 engineering and technology Sea state Kolmogorov–Smirnov test 01 natural sciences Least squares symbols.namesake [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism Residual sum of squares Histogram Computer Science::Computer Vision and Pattern Recognition symbols Probability distribution Clutter 14. Life underwater Image resolution 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IGARSS 2012 IGARSS 2012, Jul 2012, Munich, Germany IGARSS |
| Popis: | International audience; From the perspective of developing a ship detection algorithm on optical imagery, a statistical model is developed to approximate histograms from high-resolution images of the sea surface. This model is developed using an empirical approach based on analysis of hundreds of images acquired on all the oceans of the planet. Several statistical distributions are selected in agreement with the state of the art in remote sensing of sea surface and ship detection. Thumbnails of different sizes are extracted from satellite images, their histograms are then calculated. The generated histograms are approximated by the probability density functions of the different statistical distributions selected. The least-squares method is used. Reliability of the models is tested by applying the Kolmogorov- Smirnov test and analyzing the sum of squared residuals in least-squares sense. Alpha-stable distribution is retained as the best among tested models. Texture and frequency descriptors are calculated and compared with Alpha-stable parameters to assess relations binders. Reliability of the models according to the sensors, the sea state is discussed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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