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This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated with the image leading to a myopic deconvolution approach. In addition a special convex field allowing efficient hyperparameter estimation is used. The solution is based on a global a posteriori law for unknown parameters...
In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this “double compound...
Identification of materials in a planetological scene observed by an imaging spectrometer is a common problem in remote sensing. Usually the pixel size is larger than the typical size of material change over planets, leading to a linear spatial mixing. We propose here an unsupervised approach based on source separation methods to estimate the pure spectra of the components present in the observed...
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