Partitional K-means Clustering based Hybrid DCT-Vector Quantization for Image Compression

被引：0

作者：

Mahapatra, Dheeren Ku ^{[1
]}

Jena, Uma Ranjan ^{[1
]}

机构：

[1] Veer Surendra Sai Univ Technol, Dept Elect & Telecommun Engn, Burla, Odisha, India

来源：

2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT 2013) | 2013年

关键词：

Clustering; DCT; Vector Quantization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

in this paper, we propose Hybrid DCT-VQ, a lossy image compression technique based on Vector Quantization (VQ). in the proposed technique, we use the concept of energy compaction property of DCT to reduce the computational cost of codehook and to speed up the VQ process. This method is tested on set of standard test images for different sub-block sizes. The experimental simulation results infer some interesting outcomes in terms of execution time and compression ratio as compared to that of conventional VQ process.

引用

页码：1175 / 1179

页数：5

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