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Titlebook: Parallel Operator Splitting Algorithms with Application to Imaging Inverse Problems; Chuan He,Changhua Hu Book 2023 Chemical Industry Pres

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書目名稱Parallel Operator Splitting Algorithms with Application to Imaging Inverse Problems
編輯Chuan He,Changhua Hu
視頻videohttp://file.papertrans.cn/741/740985/740985.mp4
概述Addresses both algorithmic theory and numerical experiments for image restoration.Presents the numerical analysis of ill condition of imaging inverse problems.Studies comprehensively parallel operator
叢書名稱Advanced and Intelligent Manufacturing in China
圖書封面Titlebook: Parallel Operator Splitting Algorithms with Application to Imaging Inverse Problems;  Chuan He,Changhua Hu Book 2023 Chemical Industry Pres
描述Image denoising, image deblurring, image inpainting, super-resolution, and compressed sensing reconstruction have important application value in engineering practice, and they are also the hot frontiers in the field of image processing. This book focuses on the numerical analysis of ill condition of imaging inverse problems and the methods of solving imaging inverse problems based on operator splitting. Both algorithmic theory and numerical experiments have been addressed. The book is divided into six chapters, including preparatory knowledge, ill-condition numerical analysis and regularization method of imaging inverse problems, adaptive regularization parameter estimation, and parallel solution methods of imaging inverse problem based on operator splitting. Although the research methods in this book take image denoising, deblurring, inpainting, and compressed sensing reconstruction as examples, they can also be extended to image processing problems such as image segmentation, hyperspectral decomposition, and image compression. This book can benefit teachers and graduate students in colleges and universities, or be used as a reference for self-study or further study of image proce
出版日期Book 2023
關(guān)鍵詞Image restoration; Operator splitting method; ill-conditioned inverse problems; image denoising; image d
版次1
doihttps://doi.org/10.1007/978-981-99-3750-9
isbn_softcover978-981-99-3752-3
isbn_ebook978-981-99-3750-9Series ISSN 2731-5983 Series E-ISSN 2731-5991
issn_series 2731-5983
copyrightChemical Industry Press 2023
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