کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410466 679146 2009 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classified self-organizing map with adaptive subcodebook for edge preserving vector quantization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Classified self-organizing map with adaptive subcodebook for edge preserving vector quantization
چکیده انگلیسی
This paper presents a novel classified self-organizing map method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations based on modified partial distortions that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter of how large the weighting factor is. Experimental results show that the new method achieves better quality of reconstructed edge blocks and more spread out codebook and incurs a significantly less computational cost as compared to the competing methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 16–18, October 2009, Pages 3760-3770
نویسندگان
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