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Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12008/43538 Cómo citar
Título: A practical guide to multi-image alignment
Autor: Aguerrebere, Cecilia
Delbracio, Mauricio
Bartesaghi, Alberto
Sapiro, Guillermo
Tipo: Preprint
Palabras clave: Multi-image alignment, Bayesian estimators
Descriptores: Procesamiento de Señales
Fecha de publicación: 2018
Resumen: Multi - image alignment, bringing a group of images into common register, is an ubiquitous problem and the first step of many applications in a wide variety of domains. As a result, a great amount of effort is being invested in developing efficient multi-image alignment algorithms. Little has been done, however, to answer fundamental practical questions such as: what is the comparative performance of existing methods? is there still room for improvement? under which conditions should one technique be preferred over another? does adding more images or prior image information improve the registration results? In this work, we present a thorough analysis and evaluation of the main multi-image alignment methods which, combined with theoretical limits in multi-image alignment performance, allows us to organize them under a common framework and provide practical answers to these essential questions.
Descripción: Trabajo presentado en IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Citación: Aguerrebere, C, Delbracio, M, Bartesaghi, A, Sapiro, G. "A Practical guide to multi-image alignment" Publicado en: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canadá,15-20 abr., 2018, pp. 1927-1931, doi: 10.1109/ICASSP.2018.8461588.
Licencia: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Aparece en las colecciones: Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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