R
Russell M. Mersereau
Researcher at Georgia Institute of Technology
Publications - 229
Citations - 12104
Russell M. Mersereau is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Motion compensation & Image restoration. The author has an hindex of 48, co-authored 229 publications receiving 11716 citations. Previous affiliations of Russell M. Mersereau include Massachusetts Institute of Technology & Georgia Tech Research Institute.
Papers
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Book
Digital Filtering: A Computer Laboratory Textbook
TL;DR: This book provides exposure to DSP in a computer environment with a summary of the concepts basic to signal processing, nine projects and more than ten exercises to reinforce these concepts plus a library of DSP computer functions that run on personal computers using the MS-DOS operating system.
Proceedings Article
Iterative method for restoring noisy blurred images.
TL;DR: In this paper, the authors proposed a new iterative image restoration method which is capable of restoring noisy blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure.
Proceedings ArticleDOI
Fixed-analysis adaptive-synthesis filter banks
TL;DR: This approach is described as fixed analysis adaptive synthesis filter banks, which implies less coder complexity and more coder flexibility and can be compatible with existing subband wavelet encoders.
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Improved hidden Markov model classifier for SAR images
TL;DR: The proposed method applies basic principles of pattern recognition to reduce the expected misclassification rate by dynamically perturbing the HMM parameters using a constraint on a cross-entropy measure and distance separation between pairs of HMM models.
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Row-column algorithms for the evaluation of multidimensional DFT'S on arbitrary periodic smapling lattices
TL;DR: The main purpose of this work was to develop alternative algorithms which were more suitable to highly parallel machine architectures and which required less data handling than the Cooley-Tukey algorithms.