Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design
نویسندگان
چکیده
منابع مشابه
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the ...
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Vector Quantization (VQ) is one of the lossy image compression techniques. VQ comprises of three different phases: Codebook Generation, Image Encoding and Image Decoding. The performance of VQ is mainly based on the codebook generation phase. In this paper, five different codebook generation techniques namely the Simple Codebook Generation (SCG), Ordered Codebook Generation (OCG), Codebook Gene...
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In the present paper we study genetic algorithms for the codebook generation problem of vector quantization. There are two different approaches to the problem: a codebook-based and a partition-based. Both these approaches can be derived from the optimality criteria of GLA. From these, the codebookbased approach is clearly superior to the partition-based approach. The experiments show that a pur...
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Vector quantization(VQ) is an attractive technique for lossy data compression, which has been a key technology for data storage and/or transfer. So far, various competitive learning (CL) algorithms have been proposed to design optimal codebooks presenting quantization with minimized errors. However, their practical use has been limited for large scale problems, due to the computational complexi...
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ژورنال
عنوان ژورنال: Sensors
سال: 2016
ISSN: 1424-8220
DOI: 10.3390/s16111963