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Geman&McClure Stochastic Estimation for a Robust Iterative Multiframe SRR with Geman&McClure-Tikhonov Regularization
2008 Edition, December 1, 2008 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Traditionally, Super Resolution Reconstruction (SRR) is the process by which additional information is incorporated to enhance a low resolution image thereby producing a high resolution image. This paper proposes the robust SRR algorithm for any noise model...

Video Enhancement Using a Robust Iterative SRR Based on a Geman&McClure Stochastic Estimation
2009 Edition, May 1, 2009 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Most video enhancement algorithms assume that the noise model of the imaging system is known as AWGN thereby imaging process model violations often occur since the real noise model is not known in many practical applications. Robust statistics has emerged as a family of theories and...

Video enhancement using a robust iterative SRR based on a Geman&McClure stochastic estimation with a general observation model
2010 Edition, May 1, 2010 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper proposes the novel robust SRR algorithm that can be effectively applied on the sequence that are corrupted by various noise models and can be applied on the real or standard sequence. First, the proposed SRR algorithm is based on the Geman&McClure norm...

Robust Distributed Geman-McClure based Channel Estimation
2019 Edition, March 1, 2019 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Channel estimation block is the heart of any wireless communication receiver, for its requirement to properly decode the transmitted symbols from the time delayed multipath arrivals of the same. Failure of conventional least mean square (LMS) algorithms for channel...

A robust iterative multiframe SRR based on Hampel stochastic estimation with Hampel-Tikhonov regularization
2008 Edition, December 1, 2008 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Typically, super resolution reconstruction (SRR) is the process by which additional information is incorporated to enhance a noisy low resolution image hence producing a high resolution image. Although many such SRR algorithms have been proposed, almost SRR...

A Robust Iterative Multiframe Super-Resolution Reconstruction using a Huber Bayesian Approach with Huber-Tikhonov Regularization
2006 Edition, December 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

The traditional SRR (super-resolution reconstruction) estimations are based on L1 or L2 statistical norm estimation therefore these SRR methods are usually very sensitive to their assumed model of data and noise that limits their utility. This paper reviews some of these...

A robust iterative multiframe SRR based on Andrew's Sine stochastic estimation with Andrew;s Sine-Tikhonov regularization
2009 Edition, February 1, 2009 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Traditionally, the concept of Super Resolution Reconstruction (SRR) relates to a process whereby images are obtained with resolutions that are beyond the limiting factors of the uncompensated imaging system. Many such SRR algorithms have been proposed during this decade...

Optimization of a Geman-McClure like criterion for sparse signal deconvolution
2015 Edition, December 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper deals with the problem of recovering a sparse unknown signal from a set of observations. The latter are obtained by convolution of the original signal and corruption with additive noise. We tackle the problem by minimizing a least-squares fit criterion...

A Lorentzian Bayesian Approach for Robust Iterative Multiframe Super-Resolution Reconstruction with Lorentzian-Tikhonov Regularization
2006 Edition, October 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Recently, it has seen a great deal of work in the development of algorithms addressing the problem of super-resolution. Although many such algorithms have been proposed, the almost SRR (super-resolution reconstruction) estimations are based on L1 or L2 statistical norm...

A General and Adaptive Robust Loss Function
2019 Edition, June 1, 2019 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We present a generalization of the Cauchy/Lorentzian, Geman-McClure, Welsch/Leclerc, generalized Charbonnier, Charbonnier/pseudo-Huber/L1-L2, and L2 loss functions. By introducing robustness as a continuous parameter, our loss function allows algorithms built...

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