Comparison of Mamdani Fuzzy Inference System for Multiple Membership Functions
Contrast enhancement is an emerging method for image enhancement of specific application to analyze the images clearer for interpretation and analysis in the spatial domain. The goal of Contrast enhancement is to serve an input image so that resultant image is more suited to the particular applicati...
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Veröffentlicht in: | International journal of image, graphics and signal processing graphics and signal processing, 2016-09, Vol.8 (9), p.26-30 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | Contrast enhancement is an emerging method for image enhancement of specific application to analyze the images clearer for interpretation and analysis in the spatial domain. The goal of Contrast enhancement is to serve an input image so that resultant image is more suited to the particular application. Images with good steps of grays between black and white are commonly the best images for the aim of human perception, a novel approach is proposed in this paper based on fuzzy logic. Mamdani fuzzy inference system models are developed to enhance the contrast of images based on different membership functions (MFs). |
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ISSN: | 2074-9074 2074-9082 |
DOI: | 10.5815/ijigsp.2016.09.04 |