PURPOSE To measure the impact of corrupted images often found to occur in diffusion-weighted magnetic resonance imaging (DW-MRI). To propose a robust method for the correction of outliers, applicable to diffusion tensor imaging (DTI) and q-ball imaging (QBI). MATERIALS AND METHODS Monte Carlo simulations were carried out to measure the impact of outliers on DTI and QBI reconstruction in a sin...

Principal component analysis is a fundamental operation in computational data analysis, with myriad applications ranging from web search to bioinformatics to computer vision and image analysis. However, its performance and applicability in real scenarios are limited by a lack of robustness to outlying or corrupted observations. This paper considers the idealized “robust principal component anal...

Abstract. We propose several models to segment images corrupted by additive or multiplicative noise, and by a smooth field (as global intensity inhomogeneity) in a variational curve evolution approach. The proposed energies can be seen as particular K −functionals or J −functionals that arise in the theory of interpolation between spaces. In the additive case, we decompose a data function u0 in...

The Viterbi algorithm plays a fundamental role in the design of receivers for digital communication systems corrupted by Gaussian noise. This algorithm arises as the maximum likelihood sequence detector of the transmitted data symbols in several applications, including equalization for channels subject to intersymbol interference, multiuser communications, and the detection of convolutionally e...

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We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of observations is of the same magnitude as the number of variables of each observation, and the data set contains some (arbitrarily) corrupted observations. We propose a High-dimensional Robust Principal Component Analysis (...

Memory-based heuristics are a popular and effective class of admissible heuristic functions. However, corruptions to memory they use may cause these heuristics to become inadmissible. Corruption can be caused by the physical environment due to radiation and network errors, or it can be introduced voluntarily in order to decrease energy consumption. We introduce memory error correction schemes t...