Per Christian Hansen – författare
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5 produkter
Deblurring Images
Matrices, Spectra, and Filtering
Av Per Christian Hansen, James G. Nagy m. fl.
Häftad, 2006
1006 kr
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When we use a camera, we want the recorded image to be a faithful representation of the scene that we see, but every image is more or less blurry. In image deblurring, the goal is to recover the original, sharp image by using a mathematical model of the blurring process. The key issue is that some …
Discrete Inverse Problems
Insight and Algorithms
Häftad, 2010
964 kr
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Inverse problems arise when we reconstruct a sharper image from a blurred one or reconstruct the underground mass density from measurements of the gravity above the ground. When we solve an inverse problem, we compute the source that gives rise to some observed data using a mathematical model for …
Least Squares Data Fitting with Applications
Av Per Christian Hansen, Víctor Pereyra m. fl.
Inbunden, 2013
1155 kr
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As one of the classical statistical regression techniques, and often the first to be taught to new students, least squares fitting can be a very effective tool in data analysis. Given measured data, we establish a relationship between independent and dependent variables so that we can use the data …
Computed Tomography
Algorithms, Insight, and Just Enough Theory
Av Per Christian Hansen, Jakob Sauer Jørgensen m. fl.
Häftad, 2021
1076 kr
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In Computed Tomography: Algorithms, Insight, and Just Enough Theory, readers will learn about the fundamental computational methods used for image reconstruction in computed tomography (CT). Unique in its emphasis on the interplay of modeling, computing, and algorithm development, the book presents …
Rank Deficient and Discrete Ill-Posed Problems
Numerical Aspects of Linear Inversion
Häftad, 1997
1104 kr
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Here is an overview of modern computational stabilization methods for linear inversion, with applications to a variety of problems in audio processing, medical imaging, tomography, seismology, astronomy, and other areas.Rank-deficient problems involve matrices that are either exactly or nearly rank …
