Adaptive Deconvolution on the Non-negative Real Line
نویسندگان
چکیده
منابع مشابه
Non-blind Image Deconvolution with Adaptive Regularization
Ringing and noise amplification are the most dominant artifacts in image deconvolution. These artifacts can be reduced by introducing image prior into the deconvolution process. A regularization weighting factor can control strength of the regularization. Ringing and noise can be reduced significantly with the strong weighting factor, but details can be lost. We propose a nonblind image deconvo...
متن کاملOn pointwise adaptive nonparametric deconvolution
We consider estimating an unknown function f from indirect white noise observations with particular emphasis on the problem of nonparametric deconvolution. Non-parametric estimators that can adapt to unknown smoothness of f are developed. The adaptive estimators are speciied under two sets of assumptions on the kernel of the convolution transform. In particular, kernels having the Fourier trans...
متن کاملPOINTWISE PSEUDO-METRIC ON THE L-REAL LINE
In this paper, a pointwise pseudo-metric function on the L-realline is constructed. It is proved that the topology induced by this pointwisepseudo-metric is the usual topology.
متن کاملon the effect of linear & non-linear texts on students comprehension and recalling
چکیده ندارد.
15 صفحه اولA convergent non-negative deconvolution algorithm with Tikhonov regularization
We propose easy-to-implement algorithms to perform blind deconvolution of nonnegative images in the presence of noise of Poisson type. Alternate minimization of a regularized Kullback-Leibler cost function is achieved via multiplicative update rules. The scheme allows to prove convergence of the iterates to a stationary point of the cost function. Numerical examples are reported to demonstrate ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scandinavian Journal of Statistics
سال: 2017
ISSN: 0303-6898
DOI: 10.1111/sjos.12272