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Národní úložiště šedé literatury Nalezeno 3 záznamů.  Hledání trvalo 0.01 vteřin. 
Source Camera Identification Based on PRNU Invariant to Zoom
 Novozámský, Adam
In experiments with compact cameras, we found that the resulting PRNU is changing when we used the zoom in camera. The aim of this paper is analyze these changes and propose a methodology of the detection PRNU of compact cameras with zoom.
Úplný záznam
MSAR BTF Model
 Havlíček, Michal
The Bidirectional Texture Function (BTF) is the recent most advanced representation of material surface visual properties. BTF specifies the changes of visual appearance due to varying illumination and viewing conditions. Such a function might be represented by thousands of images of surface taken in given illumination and viewing conditions per sample of the material. Resulting BTF size, hundreds of gigabytes, excludes its direct rendering in graphical applications, accordingly some compression of these data is obviously necessary. This paper presents a novel probabilistic model based algorithm for realistic multispectral BTF texture modelling. This complex but efficient method combines several multispectral band limited spatial factors and corresponding range map to produce the required BTF texture. Proposed scheme enables very high BTF texture compression ratio and in addition may be used to reconstruct BTF space i.e. non-measured parts of the BTF space.
Úplný záznam
Factor Analysis of Scintigraphic Image Sequences with Integrated Probabilistic Mask of Factor Images
 Tichý, Ondřej
Factor analysis is a well established mathematical method for factor separation in the analysis of scintigraphical sequences. The results are typically an input to the next step, e.g. factor analysis for computing significant diagnostic coefficients. However, this computing highly depends on proper identification of factors and their biological meaning, which is not ensure only by factor analysis. The main issue is separation overlaping factors from themselves and from tissue background covering the whole sequence. Factor analysis highly depends on prior information which allows us to set biologically reasonable conditions to a mathematical model. In this paper, we propose a mathematical model which estimates the probability mask of each image factor and sets it as a prior information for the next step of iterative algorithm based on Variational Bayes method. The new proposed model provides more realistic estimates of factors than the standard factor analysis.
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