H
Hamid Krim
Researcher at North Carolina State University
Publications - 280
Citations - 9719
Hamid Krim is an academic researcher from North Carolina State University. The author has contributed to research in topics: Image segmentation & Wavelet transform. The author has an hindex of 33, co-authored 274 publications receiving 8934 citations. Previous affiliations of Hamid Krim include Massachusetts Institute of Technology & University of North Carolina at Chapel Hill.
Papers
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Two decades of array signal processing research: the parametric approach
Hamid Krim,Mats Viberg +1 more
TL;DR: The article consists of background material and of the basic problem formulation, and introduces spectral-based algorithmic solutions to the signal parameter estimation problem and contrast these suboptimal solutions to parametric methods.
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Time-invariant orthonormal wavelet representations
TL;DR: This work addresses the time-invariance problem for orthonormal wavelet transforms and proposes an extension to wavelet packet decompositions to achieve time invariance and preserve the orthonormality.
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A Shearlet Approach to Edge Analysis and Detection
TL;DR: This paper proposes a novel approach based on the shearlet transform: a multiscale directional transform with a greater ability to localize distributed discontinuities such as edges, which is useful to design simple and effective algorithms for the detection of corners and junctions.
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On denoising and best signal representation
TL;DR: A best basis algorithm for signal enhancement in white Gaussian noise is proposed and an estimator of the mean-square error is proposed based on a heuristic argument and the reconstruction performance based upon it is compared to that based on the Stein (1981) unbiased risk estimator.
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A generalized divergence measure for robust image registration
Yun He,A.B. Hamza,Hamid Krim +2 more
TL;DR: This paper defines a new generalized divergence measure, namely, the Jensen-Renyi (1996, 1976) divergence, and proposes a new approach to the problem of image registration based on it, to measure the statistical dependence between consecutive ISAR image frames.