An unsupervised fuzzy-neuro quantiser for image compression

An unsupervised fuzzy-neuro quantiser for image compression

We propose a competitive fuzzy-neuro model for image compression. This model is based on a new unsupervised fuzzy learning algorithm, designed for optimal training of competitive neural networks. Experimental results show that the proposed model can perform better than other well-known methods of it...

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Bibliographische Detailangaben
Hauptverfasser: Madiafi, M., Bouroumi, A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Boats
competitive neural networks
Image coding
image compression
Image reconstruction
Integrated circuits
unsupervised learning
vector quantization
Vectors
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Beschreibung
Zusammenfassung:We propose a competitive fuzzy-neuro model for image compression. This model is based on a new unsupervised fuzzy learning algorithm, designed for optimal training of competitive neural networks. Experimental results show that the proposed model can perform better than other well-known methods of its category, including FCM and IFLVQ. Typical examples of these results are presented and discussed.
DOI:10.1109/ICMCS.2012.6320219