NDLI: Enhanced fast encoding method for vector quantization by finding an optimally-ordered Walsh transform kernel

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2015 IEEE International Conference on Image Processing (ICIP)

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2004 International Conference on Image Processing, 2004. ICIP '04.

Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)

Proceedings. International Conference on Image Processing

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)

Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348)

Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269)

Proceedings of International Conference on Image Processing

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Enhanced fast encoding method for vector quantization by finding an optimally-ordered Walsh transform kernel

Content Provider	IEEE Xplore Digital Library
Author	Zhibin Pan Kotani, K. Ohmi, T.
Copyright Year	2005
Description	Author affiliation: Center for New Ind. Creation Hatchery, Tohoku Univ., Sendai, Japan (Zhibin Pan)
Abstract	In a framework of vector quantization (VQ), the encoding speed is a key issue for its practical applications. To speed up the VQ encoding process, Walsh transform is introduced in the previous work to map vectors in a k-dimensional (k-D) spatial domain into k-D Walsh domain in order to exploit the energy-compaction property of an orthogonal transform. However, there still exist a serious problem in that previous work because it just simply used the most common sequency-ordered Walsh transform kernel, which is actually not very high efficient for fast VQ encoding. In order to solve the kernel order problem in VQ encoding this paper proposes an optimal order for Walsh transform kernel based on the energy distribution of a particular codebook at each dimension in a k-D Walsh domain, which requires that the dimension with a larger energy distribution be put forward to be as a lower dimension. Experimental results confirmed that the proposed method could reduce the computational cost to 85.9% /spl sim/ 53.1% compared to the previous work so as to enhance its performance obviously.
File Size	204171
File Format	PDF
ISBN	0780391349
DOI	10.1109/ICIP.2005.1529815
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-14
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Encoding Vector quantization Kernel Euclidean distance Karhunen-Loeve transforms Image coding Electronics industry Industrial electronics Electronic mail Computational efficiency
Content Type	Text
Resource Type	Article

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