hello, I actually work with this article, Thank you very much for your help.
Regards. Le jeudi 6 février 2014 09:42:23 UTC+1, Jordi Inglada a écrit : > > milou <[email protected] <javascript:>> wrote: > > > > hello, > > on Bayesian fusion, the general formulation is: > > y = Z + E, here are the input images the multispectral and the > panchromatic one for example, and Z is the fusion image (the output image) > is this equation means the medele of Bayesian data fusion? > > > > Hi, > > Here goes a description of the method implemented in OTB which uses this > paper: > > @ARTICLE{fasbender-radoux, > author={Fasbender, D. and Radoux, J. and Bogaert, P.}, > journal={Geoscience and Remote Sensing, IEEE Transactions on}, > title={Bayesian Data Fusion for Adaptable Image Pansharpening}, > year={2008}, > month=jun , > volume={46}, > number={6}, > pages={1847 -1857}, > keywords={Bayesian data fusion;IKONOS images;SAR;adaptable image > pansharpening;hyperspectral image fusion;multispectral image;optical Earth > observation satellites;panchromatic sensor;spatial resolution multispectral > sensors;wavelet-based methods;geophysical techniques;image fusion;remote > sensing;}, > doi={10.1109/TGRS.2008.917131}, > ISSN={0196-2892},} > > ------------------------ > The Bayesian Data Fusion (BDF) method developed by Fasbender et > al. \cite{fasbender-radoux} estimates the statistical link between the > HR and the LR images in order to find the most probable value for a HR > pixel given the LR one. > > A simple sensor model for the observed pixels, > > $$ Y = g(Z) + E, $$ > > is used, where $g(.)$ are the sensor function and $E$ is random noise. > > This statistical link is represented by the conditional probability of > the high resolution multi-spectral value (the fused pixel), $z$, when > the high resolution panchromatic pixel, $y_P$, and the low resolution > multi-spectral pixel, $y_S$, are known: > > $$ f(z \vert y_S , y_P) \propto f_Z(z) \times f_{E_S} \times f_{E_P}. $$ > > The authors introduce the additional possibility of giving different > confidence levels to the panchromatic and the multi-spectral images by > slightly modifying the formulation to: > > $$ f(z \vert y_S , y_P) \propto f_Z(z) \times f_{E_S}^{2(1-w)} \times > f_{E_P}^{2w}, $$ > > where $w \in ]0,1[$ is a weight parameter. A low value for $w$ gives > more weight to the multi-spectral data. > ------------------------ > > I have copied this verbatim from a report I wrote a while ago. I think > that Julien Radoux is on this mailing list. He may correct or complete > the information. > > Jordi > > > > thank you. > > > > -- > > -- > > Check the OTB FAQ at > > http://www.orfeo-toolbox.org/FAQ.html > > > > You received this message because you are subscribed to the Google > > Groups "otb-users" group. > > To post to this group, send email to otb-users-/ > [email protected] <javascript:> > > To unsubscribe from this group, send email to > > otb-users+unsubscribe-/[email protected]<javascript:> > > For more options, visit this group at > > http://groups.google.com/group/otb-users?hl=en > > --- > > You received this message because you are subscribed to the Google > Groups "otb-users" group. > > To unsubscribe from this group and stop receiving emails from it, send > an email to otb-users+unsubscribe-/JYPxA39Uh5TLH3MbocFF+G/ > [email protected] <javascript:> > > For more options, visit https://groups.google.com/groups/opt_out. > -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/groups/opt_out.
