Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12008/43538

Título:

A practical guide to multi-image alignment

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Autor:

Aguerrebere, Cecilia
Delbracio, Mauricio
Bartesaghi, Alberto
Sapiro, Guillermo

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Tipo de documento:

Preprint

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Palabras clave:

Multi-image alignment
Bayesian estimators

Descriptores:

Procesamiento de Señales

Año de publicación:

2018

Contenido:

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)

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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.

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Departamento académico:

Procesamiento de Señales

Grupo de investigación:

Tratamiento de Imágenes

Licencia:

Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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