{"product_id":"9781025112367","title":"Statistical Methods for Image Registration and Denoising","description":"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.","brand":"Hutson Street Press","offers":[{"title":"Default Title","offer_id":46735315632369,"sku":"9781025112367","price":31.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0674\/5433\/7265\/files\/9781025112367_p0.jpg?v=1765019640","url":"https:\/\/shop.barnesandnoble.com\/products\/9781025112367","provider":"Barnes \u0026 Noble","version":"1.0","type":"link"}