ELSA: A New Image Compression Using an Expanding-Leaf Segmentation Algorithm

Authors:
Cheng-Fa Tsai;Jiun-Huang Ju
Affiliations:
Department of Management Information Systems, National Pingtung University of Science and Technology, Pingtung, Taiwan 91201;Department of Management Information Systems, National Pingtung University of Science and Technology, Pingtung, Taiwan 91201
Venue:
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Year:
2009

Citing 4
Cited 0

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Abstract

The development of multimedia has caused the heavy bandwidth load. Hence, digital content compression has become a significant topic presently. An appropriate codebook design method is a helpful and necessary principle for Vector Quantization (VQ). This work develops a new gray image compression algorithm named ELSA, witch exploits an expanding-leaf concept to determine the rough vectors (codebook) fast and utilizes the LBG for quality improvement in the end. Experimental results reveal that ELSA outperforms LBG, SOM and HSOM in terms of time-cost and image quality.