Description
Variational Methods in Imaging is a definitive resource for understanding mathematical approaches to image processing and analysis. This volume from the Applied Mathematical Sciences series provides rigorous theoretical foundations combined with practical implementations of variational techniques.
The book covers essential topics including image reconstruction, denoising, segmentation, and restoration through the lens of variational calculus and optimization theory. It explores functional analysis, partial differential equations, and modern computational methods that enable effective image enhancement and analysis.
Designed for researchers, mathematicians, and engineers, this text bridges the gap between abstract mathematical theory and real-world imaging applications. It includes detailed explanations of classical and contemporary variational models, numerical algorithms for solving imaging problems, and practical considerations for implementation in scientific and industrial settings.
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