Image Compression Method
Sunanda Kisanrao Kapde1, S. V. Patil2
1Sunanda Kisanrao Kapde, Lecturer, E & TC Department, B.l. Patil Polytechnic Khopoli, Maharashtra, India.
2Mr. S.V. Patil, Associate professor, E & TC Department, J.T. Mahajan College of  Engg, Faizpur Maharashtra, India.
Manuscript received on January 30, 2013. | Revised Manuscript received on February 16, 2013. | Manuscript published on February 28, 2013. | PP: 426-429 | Volume-2 Issue-3, February 2013.  | Retrieval Number: C1166022313/2013©BEIESP

Open Access | Ethics and Policies | Cite
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Data transmission and storage cost money. The more information being dealt with, the more it costs. In spite of this, most digital data are not stored in the most compact form. Rather, they are stored in whatever way makes them easiest to use. Data compression is the general term for the various algorithms and programs developed to address this problem. A compression program is used to convert data from an easy-to-use format to one optimized for compactness. Here two algorithms were selected namely, the original block truncation coding (BTC) and Absolute Moment block truncation coding (AMBTC) and a comparative study was performed. The results have shown that the ATBTC algorithm outperforms the BTC. It has been show that the image compression using AMBTC provides better image quality than image compression using BTC at the same bit rate. Moreover, the AMBTC is quite faster compared to BTC.
Keywords: BTC, AMBTC, Q level quantizer, image compression; mean, standard deviation.