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Autor(en): 
  • Changhua Hu
  • Chuan He
  • Parallel Operator Splitting Algorithms with Application to Imaging Inverse Problems 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  August 2023  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Bildverarbeitung / Digitale Signalverarbeitung (DSP) / ill-conditionedinverseproblems / imagecompressedsensing / ImageDeblurring / imagedenoising / ImageInpainting / ImageRestoration
    ISBN:  9789819937493 
    EAN-Code: 
    9789819937493 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 18 mm 
    Gewicht:  494 gr 
    Seiten:  216 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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 processing technology engineers.

      



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