Variants of Self-Organizing Maps
Applications in Image Quantization and Compression
The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this work, two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight ch…
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Produktdetails
Weitere Autoren: Lee, Chung-Nan / Hsieh, Chaur-Heh
- ISBN: 978-3-8383-2436-4
- EAN: 9783838324364
- Produktnummer: 37833029
- Verlag: LAP Lambert Academic Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2010
- Seitenangabe: 80 S.
- Masse: H22.0 cm x B15.0 cm x D0.5 cm 137 g
- Abbildungen: Paperback
- Gewicht: 137
Über den Autor
Chao-Hung Wang received his Ph.D. degree in Department of Computer Science and Engineering in 2009 from National Sun Yat-Sen University, Kaohsiung, Taiwan. His research interests include image processing, vector quantization, pattern recognition, and image retrieval. His advisors are Prof. Chung-Nan Lee and Prof. Chaur-Heh Hsieh.
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