DocumentCode
3548720
Title
Vector quantization of images using fractal dimensions
Author
Moyamoto, Takayuki ; Suzuki, Yukinori ; Saga, Sato ; Maeda, Junji
Author_Institution
Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan
fYear
2005
fDate
28-30 June 2005
Firstpage
214
Lastpage
217
Abstract
In conventional vector quantization (VQ), for example, generalized Lloyd algorithm (GLA), an image is divided into blocks that are all the same size. This uniform division could be redundant. Furthermore, it could not attain both a high compression rate and high quality of encoded image. We propose a new method of VQ in which the block size to divide an image is determined by a local fractal dimension (LDF). Computational experiments were carried out to show the effectiveness of the method. Results of experiments showed that a compression rate of the proposed method is higher than that by the GLA under the condition that PSNR (Peak Signal-to-Noise Ratio) is more than 35.0 dB. Therefore, the proposed method is useful for practical image compression.
Keywords
generalisation (artificial intelligence); image coding; image denoising; vector quantisation; encoded image; fractal dimension; generalized Lloyd algorithm; image compression; peak signal-to-noise ratio; vector quantization; Asynchronous transfer mode; B-ISDN; Clustering algorithms; Computer science; Decoding; Fractals; Image coding; PSNR; Pixel; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Soft Computing in Industrial Applications, 2005. SMCia/05. Proceedings of the 2005 IEEE Mid-Summer Workshop on
Print_ISBN
0-7803-8942-5
Type
conf
DOI
10.1109/SMCIA.2005.1466975
Filename
1466975
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