Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images
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http://hdl.handle.net/10045/101124
Título: | Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images |
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Autor/es: | Arnal, Josep | Súcar Segarra, Luis Beltrán |
Grupo/s de investigación o GITE: | Computación de Altas Prestaciones y Paralelismo (gCAPyP) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial |
Palabras clave: | Image enhancement | Noise filtering | Mixed Gaussian and impulsive noise | Fuzzy logic |
Área/s de conocimiento: | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | 28-dic-2019 |
Editor: | MDPI |
Cita bibliográfica: | Arnal J, Súcar L. Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images. Applied Sciences. 2020; 10(1):243. doi:10.3390/app10010243 |
Resumen: | To decrease contamination from a mixed combination of impulse and Gaussian noise on color digital images, a novel hybrid filter is proposed. The new technique is composed of two stages. A filter based on a fuzzy metric is used for the reduction of impulse noise at the first stage. At the second stage, to remove Gaussian noise, a fuzzy peer group method is applied on the image generated from the previous stage. The performance of the introduced algorithm was evaluated on standard test images employing widely used objective quality metrics. The new approach can efficiently reduce both impulse and Gaussian noise, as much as mixed noise. The proposed filtering method was compared to the state-of-the-art methodologies: adaptive nearest neighbor filter, alternating projections filter, color block-matching 3D filter, fuzzy peer group averaging filter, partition-based trimmed vector median filter, trilateral filter, fuzzy wavelet shrinkage denoising filter, graph regularization filter, iterative peer group switching vector filter, peer group method, and the fuzzy vector median method. The experiments demonstrated that the introduced noise reduction technique outperforms those state-of-the-art filters with respect to the metrics peak signal to noise ratio (PSNR), the mean absolute error (MAE), and the normalized color difference (NCD). |
Patrocinador/es: | This work was funded by the Spanish Ministry of Science, Innovation, and Universities (grant RTI2018-098156-B-C54) and it was co-financed with FEDER funds. |
URI: | http://hdl.handle.net/10045/101124 |
ISSN: | 2076-3417 |
DOI: | 10.3390/app10010243 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/app10010243 |
Aparece en las colecciones: | INV - gCAPyP - Artículos de Revistas |
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