{"product_id":"introduction-to-inverse-problems-in-imaging-9780367467869","title":"Introduction to Inverse Problems in Imaging","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis second edition of Introduction to Inverse Problems in Imaging provides an accessible introduction to linear inverse problems, approximate solution methods, and practical applications in imaging. It includes new chapters on edge-preserving and sparsity-enforcing regularization, maximum likelihood methods, and Bayesian regularization for Poisson data. The book is suitable for students from different backgrounds with a rudimentary understanding of analysis, geometry, linear algebra, probability theory, and Fourier analysis. It focuses on presenting easily implementable and fast solution algorithms and is accompanied by numerical examples. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 342 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 29 January 2024\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis second edition of Introduction to Inverse Problems in Imaging is a comprehensive guide for advanced undergraduate and graduate students in physics, computer science, mathematics, and engineering. It provides a thorough exploration of linear inverse problems, their approximate solution methods, and practical applications in imaging. The book has been fully updated throughout, incorporating several new chapters on edge-preserving and sparsity-enforcing regularization, maximum likelihood methods, and Bayesian regularization for Poisson data.\u003cbr\u003e\u003cbr\u003eThe authors have aimed to keep the mathematical treatment at a level that is accessible to students from diverse backgrounds, requiring only a basic understanding of analysis, geometry, linear algebra, probability theory, and Fourier analysis. The focus is on presenting easily implementable and efficient solution algorithms, accompanied by numerical examples throughout the text.\u003cbr\u003e\u003cbr\u003eThe book serves as an accessible introduction to the topic, while simultaneously delving into the mathematical complexities involved. It covers key concepts such as ill-posedness and its cure, providing readers with a solid foundation for understanding the rapidly growing literature on inverse problems. With its interdisciplinary nature and wide-ranging applications, Introduction to Inverse Problems in Imaging is a valuable resource for students and researchers in the fields of physics, computer science, mathematics, and engineering.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 780g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 177 x 254 x 20 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780367467869\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 2 ed\u003c\/p\u003e","brand":"M.Bertero,P.Boccacci,Christine De Mol","offers":[{"title":"Paperback \/ softback","offer_id":45179498004730,"sku":"9780367467869","price":48.54,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_6de71bbc-86d7-4066-8711-ce4ff57a8095.jpg?v=1707754489","url":"https:\/\/shulphink.com\/products\/introduction-to-inverse-problems-in-imaging-9780367467869","provider":"Shulph Ink","version":"1.0","type":"link"}