Modeliranje slik SAR z avto-binomskim modelom

doktorska disertacija

Marko Hebar (Author), Žarko Čučej (Mentor), Dušan Gleich (Co-mentor)

Abstract

Doktorska disertacija predstavlja odpravljanje pegastega šuma z modeliranjem in izločanjem informacij iz posnetkov SAR (ang. Synthetic Aperture Radar - SAR), ki je izvedeno z Bayesovim sklepanjem. Novost, ki jo predstavljam v doktorski disertaciji je uporaba avto-binomskega modela pri Bayesovem sklepanju prvega reda, kjer ga za apriorno verjetnost uporabimo pri modeliranju posnetka. Verjetje v Bayesovem sklepanju prvega reda modelira pegasti šum, ki ga opišemo z gama porazdelitvijo. Odpravljanje pegastega šuma je izvedeno s cenilko največje verjetnosti MAP (ang. maximum a posteriori - MAP), ki jo je analitično zelo težko rešiti, zato z avto-binomskim modelom uporabimo aproksimacijo z diferencialom. Parametri avto-binomskega modela se določijo z Bayesovim sklepanjem drugega reda. Robovi v posnetku se določijo z algoritmom rasti regij. Glede na koeficient variacije so ločene homogene od heterogenih regije in adaptivno prilagajanje okolice avto binomskega modela. Eksperimentalni rezultati so pokazali, da predstavljena metoda zelo dobro modelira teksture in ima dobre lastnosti odpravljanja pegastega šuma in zelo dobro modelira teksture v realnih posnetkih SAR.

Keywords

radarske slike;modeliranje slik;avto-binomski model;pegasti šum;odpravljanje pegastega šuma;Bayesovo sklepanje;

Data

Language:	Slovenian
Year of publishing:	2010
Source:	Maribor
Typology:	2.08 - Doctoral Dissertation
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[M. Hebar]
UDC:	004.93:621.396.963
COBISS:	254665472
Views:	2377
Downloads:	137
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Modeling SAR images with auto-binomial model
Secondary abstract:	This dissertation presents a model based despeckling of Synthetic Aperture Radar (SAR) images using Bayesian analysis. The use of first order of Bayesian inference with auto-binomial model is used for SAR image despeckling. The novelty of dissertation is an auto-binominal model, which models a prior probability density function (pdf). Speckle models the likelihood pdf, represented by Gamma distribution. An analytical solution of a maximum a posteriori (MAP) estimate using an auto-binominal prior is difficult to compute. Therefore, the approximate solution of MAP estimate is proposed using the differential. The best auto-binomial model is determined by the second order Bayesian inference. The edges in the SAR images are detected using region borders, which have statistically different properties. Coefficient of variation is used to distinguish between homogeneous and heterogeneous regions. The experimental results show that the proposed method is one of the best algorithms for the textural features extraction and its capability of speckle removing. The proposed despeckling method is comparable with state-of-the-art methods and well models textures presented in real SAR images.
Secondary keywords:	image modeling;SAR images;Synthetic Aperture Radar images;despeckling;Bayesian analysis;auto-binomial model;
URN:	URN:SI:UM:
Type (COBISS):	Dissertation
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko
Pages:	160 str.
Keywords (UDC):	science and knowledge;organization;computer science;information;documentation;librarianship;institutions;publications;znanost in znanje;organizacije;informacije;dokumentacija;bibliotekarstvo;institucije;publikacije;prolegomena;fundamentals of knowledge and culture;propaedeutics;prolegomena;splošne osnove znanosti in kulture;computer science and technology;computing;data processing;računalniška znanost in tehnologija;računalništvo;obdelava podatkov;application-oriented computer-based techniques;računalniške tehnike za namensko rabo;aplikativno usmerjene računalniško podprte tehnike;pattern information processing;obdelava informacij v vzorcih;applied sciences;medicine;technology;uporabne znanosti;medicina;tehnika;engineering;technology in general;inženirstvo;tehnologija na splošno;mechanical engineering in general;nuclear technology;electrical engineering;machinery;strojništvo;electrical engineering;elektrotehnika;
ID:	994580