Título

On the comparison of different Kernel functionals and neighborhood geometry for Nonlocal Means filtering

Autor

JOSE ISMAEL DE LA ROSA VARGAS

José de Jesús Villa Hernández

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Materias

INGENIERÍA Y TECNOLOGÍA - (CTI) Image filtering Nonlocal means Kernel functionals Sparse learning techniques Collaborative filtering

Resumen o descripción

The present work proposes a review and comparison of different Kernel functionals and neighborhood geometry for Nonlocal Means (NLM) in the task of digital image filtering. Some different alternatives to change the classical exponential kernel function used

in NLM methods are explored. Moreover, some approaches that change the geometry of the neighborhood and use dimensionality reduction of the neighborhood or patches onto principal component analysis (PCA) are also analyzed, and their performance is compared with respect to the classic NLM method. Mainly, six approaches were compared using quantitative and qualitative evaluations, to do this an homogeneous framework has been established using the same simulation platform, the same computer, and same conditions for the initializing parameters.

Producción Científica de la Universidad Autónoma de Zacatecas UAZ

Fecha de publicación

enero de 2018

Tipo de publicación

Artículo

Recurso de información

http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1712

1380-7501

1573-7721

Formato

application/pdf

Idioma

Inglés

Audiencia

Público en general

Repositorio Orígen

Repositorio Institucional Caxcán

Descargas

0