Titlebook: Handbook of Mathematical Methods in Imaging; Otmar Scherzer Living reference work 20200th edition

Anthrp

Local Smoothing Neighborhood Filters,rhood filters are usually preferred. These filters perform an average of neighboring pixels, but only under the condition that their gray level is close enough to the one of the pixel in restoration. This very popular method unfortunately creates shocks and staircasing effects. It also excessivelly

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Mathematical Methods in PET and SPECT Imaging,e used in PET and SPECT image reconstruction, respectively. Using a new method for deriving transform pairs in one and two dimensions, we derive the inverse Radon transform and the IART. Furthermore, we discuss an alternative approach for computing the Hilbert transform using cubic splines. This new

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Mathematical Modeling of Optical Coherence Tomography,es high-resolution images of the inner structure of biological tissues. Images are obtained by measuring the time delay and the intensity of the backscattered light from the sample considering also the coherence properties of light. The scattering problem is considered for a weakly scattering medium

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spinal-stenosis

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1FAWN

Optical Flow,sents the corresponding motion induced on the image plane. This paper describes the basic problems and concepts related to optical flow estimation together with mathematical models and computational approaches to solve them. Emphasis is placed on common and different modeling aspects and to relevant

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Regularization Methods for Ill-Posed Problems,linear ill-posed inverse problems. The focus is on Tikhonov type variational regularization applied to nonlinear ill-posed operator equations formulated in Hilbert and Banach spaces. The chapter begins with the consideration of the classical approach in the Hilbert space setting with quadratic misfi