Results 201 to 210 of about 323,867 (242)
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SIAM Journal on Applied Mathematics, 2001
Summary: Blind deconvolution seeks to deblur an image without knowing the cause of the blur. Iterative methods are commonly applied to that problem, but the iterative process is slow, uncertain, and often ill-behaved. This paper considers a significant but limited class of blurs that can be expressed as convolutions of two-dimensional symmetric Lévy ...
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Summary: Blind deconvolution seeks to deblur an image without knowing the cause of the blur. Iterative methods are commonly applied to that problem, but the iterative process is slow, uncertain, and often ill-behaved. This paper considers a significant but limited class of blurs that can be expressed as convolutions of two-dimensional symmetric Lévy ...
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Near optimal blind deconvolution
ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003A solution is proposed for blind deconvolution problems, i.e. the estimation of the impulse response of an unknown discrete-time channel given the output data sequence and statistical information on the input sequence. The solution approaches the optimal one when the input sequence is independent and identically distributed and the channel distortion ...
Sandro Bellini, Fabio Rocca
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Iterative method for blind deconvolution
Journal of Electronic Imaging, 1994We present a new technique for blind restoration of images degraded by a smooth, spatially-invariant, zero-phase blur function. The restored image is obtained by using the information preseived in the phase of the blurred image to form an initial estimate. Successive estimates are produced by iteratively refining the initial estimate.
Tamer F. Rabie +2 more
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Blind deconvolution of echosounder envelopes
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002Ocean bottom classification performed using an an installed technology base requires compensation for the existing technology's constraints, including the fact that the digitized signal is the envelope of the convolution of the bottom's impulse response and the source ping. We present a method by which the impulse response coefficients may be estimated
David A. Caughey, R. Lynn Kirlin
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Blind Deconvolution with Sparse Priors on the Deconvolution Filters
2006In performing blind deconvolution to remove reverberation from speech signal, most acoustic deconvolution filters need a great many number of taps, and acoustic environments are often time-varying. Therefore, deconvolution filter coefficients should find their desired values with limited data, but conventional methods need lots of data to converge the ...
Hyung-Min Park +3 more
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Total variation blind deconvolution
IEEE Transactions on Image Processing, 1998In this paper, we present a blind deconvolution algorithm based on the total variational (TV) minimization method proposed. The motivation for regularizing with the TV norm is that it is extremely effective for recovering edges of images as well as some blurring functions, e.g., motion blur and out-of-focus blur.
Tony F. Chan, Chiu-Kwong Wong
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Blind deconvolution for multidimensional images
Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002There are a number of technical situations where inversion of measured data involves blind deconvolution (i.e. the point spread function is unknown a priori) in three (or more) dimensions. We show that a unique solution exists for three-dimensional (3D) blind deconvolution for a particular sampling of the Fourier transform of a blurred image whose ...
Rick P. Millane +2 more
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Kuicnet Algorithms for Blind Deconvolution
Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378), 1998We show how the recently-developed KuicNet method for instantaneous blind source separation can be extended to the blind deconvolution task. The proposed algorithm has a simple form and is effective in deconvolving source signals with non-zero kurtoses from a linear filtered version of the source sequence.
S.C. Douglas, S.-Y. Kung
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Bayesian techniques for blind deconvolution
IEEE Transactions on Communications, 1996The paper presents a new algorithm for blind deconvolution in digital communication which performs joint input and channel estimation. The blind deconvolution problem is formulated as a nonlinear and non-Gaussian fixed-lag mean square error filtering problem, and the extended Bayesian filter is derived as a suboptimal recursive estimator.
Gen-Kwo Lee +2 more
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Compact multiframe blind deconvolution
Optics Letters, 2011We describe a multiframe blind deconvolution (MFBD) algorithm that uses spectral ratios (the ratio of the Fourier spectra of two data frames) to model the inherent temporal signatures encoded by the observed images. In addition, by focusing on the separation of the object spectrum and system transfer functions only at spatial frequencies where the ...
Douglas A, Hope, Stuart M, Jefferies
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