and Analysis - Variational, PDE, wavelet, and stochastic methods
Overview and some images of the book
Image processing has traditionally been built on the machinery of Fourier and spectral analysis; however, in the past few decades numerous novel competing methods and tools have emerged. These diversified approaches, although seemingly distinct, are in fact intrinsically connected. The authors integrate this diversity of modern image processing approaches by revealing the few common threads connecting them. Some newer emergent integration efforts have also been highlighted and analyzed.
Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic
Methods is systematic and well organized. The authors first investigate
the geometric, functional, and atomic structures of images and then rigorously
develop and analyze several image processors. The book is comprehensive
and integrative, covering the four most powerful classes of mathematical
tools in contemporary image analysis and processing while exploring their
intrinsic connections and integration. The material is balanced in theory
and computation, following a solid theoretical analysis of model building
and performance with computational implementation and numerical examples.
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