Absolute Moment Block Truncation Coding For Color Image Compression
D.Harihara Santosh1, U.V.S. Sitarama Varma2, K.S.K Chaitanya Varma3, Meena Jami4, V.V.N.S Dileep5
1Mr. D. Hari Hara Santosh, B.Tech. and M.Tech Degrees, JNT University, Hyderabad (Telangana), India.
2Mr. U.V.S Sitarama Varma, Assistant Professor, MVGR College of Engineering, Vizianagaram (A.P), India.
3Mr. Sri Krishna Chaitanya Varma, B.Tech, MVGR College of Engineering, JNT University, Kakinada (A.P), India.
4Miss. Meena Jami, B.Tech, MVGR College of Engineering, JNT University, Kakinada (A.P), India.
5Mr. V.V.N.S. Dileep, B.Tech, MVGR College of Engineering, JNT University, Kakinada (A.P), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 53-59 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0780052613/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper Color image data compression using absolute moment block truncation coding scheme (AMBTC) is implemented. This compression technique reduces the computational complexity and achieves the optaimum minimum mean square error and PSNR. It is an improvised version of BTC, obtained by preserving absolute moments. AMBTC is an encoding technique that preserves the spatial details of digital images while achieving a reasonable compression ratio. The simulation results obtained indicate that both the computational complexity of and the reconstructed image quality obtained using AMBTC algorithm are better than those obtainable with other existing BTC algorithms.
Keywords: Absolute Moment Block Truncation Coding, Computational Complexity.
Scope of the Article: Image Processing and Pattern Recognition