Adaptive parameter selection for block wavelet-thresholding deconvolution
نویسندگان
چکیده
منابع مشابه
Adaptive Parameter Selection for Block Wavelet-Thresholding Deconvolution
In this paper, we propose a data-driven block thresholding procedure for waveletbased non-blind deconvolution. The approach consists in appropriately writing the problem in the wavelet domain and then selecting both the block size and threshold parameter at each resolution level by minimizing Stein’s unbiased risk estimate. The resulting algorithm is simple to implement and fast. Numerical illu...
متن کاملStein block thresholding for wavelet-based image deconvolution
Abstract: In this paper, we propose a fast image deconvolution algorithm that combines adaptive block thresholding and Vaguelet-Wavelet Decomposition. The approach consists in first denoising the observed image using a wavelet-domain Stein block thresholding, and then inverting the convolution operator in the Fourier domain. Our main theoretical result investigates the minimax rates over Besov ...
متن کاملSelection of Varying Spatially Adaptive Regularization Parameter for Image Deconvolution
The deconvolution in image processing is an inverse illposed problem which necessitates a trade-off between delity to data and smoothness of a solution adjusted by a regularization parameter. In this paper we propose two techniques for selection of a varying regularization parameter minimizing the mean squared error for every pixel of the image. The rst algorithm uses the estimate of the square...
متن کاملAdaptive Parameter Selection for Total Variation Image Deconvolution
In this paper, we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in each iteration. Numerical results are shown to illustrate the performance of the proposed method. AMS subject classifications: 65K10, 68U10
متن کاملDeconvolution by thresholding in mirror wavelet bases
The deconvolution of signals is studied with thresholding estimators that decompose signals in an orthonormal basis and threshold the resulting coefficients. A general criterion is established to choose the orthonormal basis in order to minimize the estimation risk. Wavelet bases are highly sub-optimal to restore signals and images blurred by a low-pass filter whose transfer function vanishes a...
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: IFAC Proceedings Volumes
سال: 2013
ISSN: 1474-6670
DOI: 10.3182/20130703-3-fr-4038.00148