Psykologi & pedagogik
Pocket
Statistical Methods for Image Registration and Denoising
Matthew D Sambora
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Uppskattad leveranstid 7-12 arbetsdagar
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This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing a novel method that exploits local correlations to improve the performance of projection-based image registration algorithms. The dissertation also extends the bounds on image registration performance for both projection-based and full-frame image registration algorithms and extends the Barankin bound from the one-dimensional case to the problem of two-dimensional image registration. It is demonstrated that in some instances, the Cramer-Rao lower bound is an overly-optimistic predictor of image registration performance and that under some conditions, the Barankin bound is a better predictor of shift estimator performance. The research also looks at the related problem of single-frame image denoising using block-based methods. The research introduces three algorithms that operate by identifying regions of interest within a noise-corrupted image and then generating noise free estimates of the regions as averages of similar regions in the image.
- Format: Pocket/Paperback
- ISBN: 9781288286348
- Språk: Engelska
- Antal sidor: 156
- Utgivningsdatum: 2012-11-12
- Förlag: Biblioscholar