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pro vyhledávání: '"Howard Kaufman"'
Autor:
S. Koch, Howard Kaufman
Publikováno v:
IFAC Proceedings Volumes. 25:477-480
Blurred and noisy images can often be represented as nonstationary two-dimensional (2-D) stochastic processes that can be modeled by a set of linear state equations with space-varying coefficients. This paper presents an algorithms based on the Exten
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 4(4)
Image restoration based upon unrealistic homogeneous image and blur models can result in highly inaccurate estimates with excessive ringing. Thus, it is important at each pixel location to restore the image using the particular image and blur paramet
Autor:
Howard Kaufman, Kevin T. Damour
Publikováno v:
Image Processing Algorithms and Techniques II.
A model-based Kalman estimator is developed for spatial-temporal filtering of noise and other degradations in velocity and depth maps derived from image sequences or cinema. As an illustration of the proposed procedures, edge information from image s
Publikováno v:
IEEE Transactions on Automatic Control. 28:745-756
Estimation of image pixel density can be performed using a reduced update Kalman filter provided that a mathematical model for the image generating process is available. To this effect various algorithms suitable for identifying the parameters of aut
Publikováno v:
ICASSP
Scopus-Elsevier
Scopus-Elsevier
An optimal statistical parameter estimation technique is presented for the identification of unknown image and blur model parameters. The development leads to an autoregressive moving average (ARMA) model identification problem, where the image model
Publikováno v:
1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.
A two-dimensional recursive algorithm based upon the use of multiple models is described for the problem of nonstationary image processing. Of importance is the doubly stochastic representation resulting from the modelling of the transition of the ap
This paper presents initial results on spatially variant recursive estimation of images. Parameters of block-wise constant recursive model are identified on noise free data. The models are then used to design reduced update Kalman filters which are a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f787ad864b9769452a5e50d22ba0efa3
https://doi.org/10.21236/ada054115
https://doi.org/10.21236/ada054115