Fundamentals of digital image processing
Fundamentals of digital image processing
Multidimensional Digital Signal Processing
Multidimensional Digital Signal Processing
Digital Image Restoration
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Improved Methods of Maximum a Posteriori Restoration
IEEE Transactions on Computers
Bayesian Methods in Nonlinear Digital Image Restoration
IEEE Transactions on Computers
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
On the cepstrum of two-dimensional functions (Corresp.)
IEEE Transactions on Information Theory
Kalman filtering in two dimensions
IEEE Transactions on Information Theory
Real-time restoration of images degraded by uniform motion blur in foveal active vision systems
IEEE Transactions on Image Processing
Identification and restoration of spatially variant motion blurs in sequential images
IEEE Transactions on Image Processing
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In this paper, we address the problem of restoring photographic images degraded by motion blur and film-grain noise. Based on the one-dimensional particle filter, a new approach is proposed for restoration under space-invariant as well as space-variant blurring conditions. The method works by propagating the samples of the probability distribution through an appropriate state model. The weights of the samples are computed using the observation model and the degraded image. The samples and their corresponding weights are used to estimate the original image. In order to verify and validate the proposed approach, the method is tested on several images, both synthetic and real.