An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method.
Guardado en:
Autores principales: | Shao Chonglei, Kaur Preet, Kumar Rajeev |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
De Gruyter
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/721eb0b503a84d3a9cc482bded6fc035 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
por: Suneetha Akula, et al.
Publicado: (2020) -
The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
por: Shihab Hamad Khaleefah, et al.
Publicado: (2021) -
Instance Reduction for Avoiding Overfitting in Decision Trees
por: Amro Asma’, et al.
Publicado: (2021) -
Shock filter coupled with a high-order PDE for additive noise removal and image quality enhancement
por: Simo Thierry, et al.
Publicado: (2021) -
Weak implicative filters in quasi-ordered residuated systems
por: Romano,Daniel A.
Publicado: (2021)