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Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera s/n, Valencia, 46022, Spain

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1 Papers

Fuzzy Inference System in a Local Eigenvector Based Color Image Smoothing Framework

Topics: Digital Image Enhancement; Digital Filtering; Quality Enhancement; Digital Imaging and Rendering

Authors: Khleef Almutairi ^{1

;

2} , Samuel Morillas ¹ and Pedro Latorre-Carmona ³

Affiliations: ¹ Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera s/n, Valencia, 46022, Spain , ² Mathematics Department, Faculty of Science, Albaha University, Suadi Arabia , ³ Departmento de Ingeniería Informática, Universidad de Burgos, Avda. Cantabria s/n, Burgos, 09006, Spain

Digital Object Identifier: 10.5220/0011966900003497

Proceedings of IMPROVE 2023, ISBN: 978-989-758-642-2

Quick Abstract

Noise filtering in colour images is a complex task since it is essential to distinguish between structural and noise information in the image. It would therefore be important to simultaneously remove noise while keeping the original image details. This paper proposes a method based on a fuzzy inference system to eliminate noise and retrieve original image details. Images are transformed from an RGB space to an eigenvector based space and this transformation is fed to the fuzzy system. Results confirm the validity of the approach, its superior performance when compared to the eigenvector based framework it is based on, and its competitive behaviour when compared to other state-of-the-art methods.