<p>This book contains both a synthesis and mathematical analysis of a wide set of algorithms and theories whose aim is the automatic segmenΒ tation of digital images as well as the understanding of visual perception. A common formalism for these theories and algorithms is obtained in a variational f
Variational methods in image segmentation: with seven image processing experiments
β Scribed by Jean-Michel Morel, Sergio Solimini
- Publisher
- BirkhΓ€user Boston
- Year
- 1994
- Tongue
- English
- Leaves
- 134
- Series
- Progress in Nonlinear Differential Equations and Their Applications
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This text contains a synthesis and a mathematical analysis of a wide set of algorithms and theories whose aim is the automatic segmentation of digital images as well as the understanding of visual perception. A common formalism for these theories and algorithms is obtained in variational form. Thanks to the formalization, mathematical questions about the soundness can be raised and answered. Perception theory has to deal with the complex interaction between regions and "edges" (or boundaries) in an image; in the variational segmentation energies, "edge" terms compete with "region" terms in a way which is intended to impose regularity on both regions and boundaries. The first part of the book presents a unified presentation of the evidence in favour of the conjecture. It is proven that the competition of one-dimensional and two-dimensional energy terms in a variational formulation cannot create fractal-like behaviour for the edges. The proof of regularity for the edges of a segmentation constantly involves concepts from geometric measure theory, which proves to be central in image processing theory. The second part of the book provides a fast and self-contained presentation of the classical theory of rectifiable sets (the "edges") and unrectifiable sets ("fractals").
π SIMILAR VOLUMES
<p>This book contains both a synthesis and mathematical analysis of a wide set of algorithms and theories whose aim is the automatic segmenΒ tation of digital images as well as the understanding of visual perception. A common formalism for these theories and algorithms is obtained in a variational f
About This Book Design automated image-processing solutions and speed up image-processing tasks with ImageJ Create quality and intuitive interfaces for image processing by developing a basic framework for ImageJ plugins. Tackle even the most sophisticated datasets and complex images
<p>Variational Methods in Image Processing presents the principles, techniques, and applications of variational image processing. The text focuses on variational models, their corresponding Euler-Lagrange equations, and numerical implementations for image processing. It balances traditional computat
<p>Image segmentation consists of dividing an image domain into disjoint regions according to a characterization of the image within or in-between the regions. Therefore, segmenting an image is to divide its domain into relevant components. The efficient solution of the key problems in image segment