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This long-established and well-received monograph offers an integral view of image processing - from image acquisition to the extraction of the data of interest – written by a physical scientists for other scientists.
Supplements discussion of the general concepts is supplemented with examples from applications on PC-based image processing systems and ready-to-use implementations of important algorithms.
Completely revised and extended, the most notable extensions being a detailed discussion on random variables and fields, 3-D imaging techniques and a unified approach to regularized parameter estimation.
This successful, practical guide uses the concepts and mathematics familiar to students of the natural sciences to provide them with a working knowledge of modern techniques of digital image processing. It takes readers from the fundamentals to current research in the field and teaches them how to use them for data gathering and interpretation in their science.
Foundation.- Applications and Tools.- Image Representation.- Random Variables and Fields.- Neighborhood Operations.- Multiscale Representation.- Image Formation and Preprocessing.- Quantitative Visualization.- Image Formation.- 3-D Imaging.- Digitization, Sampling, Quantization.- Pixel Processing.- Feature Extraction.- Averaging.- Edges.- Simple Neighborhoods.- Motion.- Texture.- Image Analysis.- Segmentation.- Regularization and Modeling.- Morphology.- Shape Presentation and Analysis.- Classification.