Titlebook: Nonlinear Eigenproblems in Image Processing and Computer Vision; Guy Gilboa Book 2018 Springer International Publishing AG, part of Spring

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Guy GilboaThe first book on this topic, relating the new theory to image processing and computer vision applications.Integrates deep mathematical concepts from various fields into a coherent manuscript with plo

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Applications Using Nonlinear Spectral Processing,cement, and image fusion. This area is currently investigated and developed. A main theme is that following the image decomposition one can use very basic operations of attenuating, enhancing, and mixing certain spectral bands. Thus, a single framework with a solid theory can have very diverse appli

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Numerical Methods for Finding Eigenfunctions, In the variational context, the research is quite preliminary. We outline the method of Hein and Buhler, based on the Rayleigh quotient. We present in more detail a recent work by Raz Nossek and the author where a flow is used to solve the problem. This can be generalized in various ways. A general

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,Beyond Convex Analysis—Decompositions with Nonlinear Flows,as nonlinear operators, and the coarsening scale space they induce can be analyzed in a spectral manner. We provide some basic assumptions that help us solve the new spectral decomposition problem. Essentially, a common decay profile is sought in order to decompose the image. It is shown that this g

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Relations to Other Decomposition Methods, wavelets are given, showing one can recover wavelet processing within this framework. In the specific case of Haar wavelet, which is actually a small subset of the eigenfunction of TV, it is shown how the spectral TV can adapt better to the signal. A numerical example shows that fewer elements are