Visually Lossless Compression for Color Images with Low Memory Requirement using Lossless Quantization
Mary Jansi Rani. Y1, Pon. L.T. Thai2, John Peter. K3
1Mary Jansi Rani.Y, Computer Science, Vins Christian College of Engineering, Anna University,Nagercoil, India.
2Pon. L.T. Thai, Computer Science, Vins Christian College of Engineering, Anna University,Nagercoil, India.
3John Peter. K, Information Technology, Vins Christian College of Engineering, Anna University,Nagercoil, India.
Manuscript received on July 01, 2012. | Revised Manuscript received on July 04, 2012. | Manuscript published on July 05, 2012. | PP: 156-159 | Volume-2, Issue-3, July 2012. | Retrieval Number: C0734052312 /2012©BEIESP
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© The Authors. Published By: 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 a novel method is proposed to compress color images with no loss in quality. For the compression of the color image non uniform quantizers are used. These non uniform quantizers are implemented for different areas. The blocks are classified, predicted, encoded and decoded to get the resulted output. The blocks are classified based on principle component analysis. The output provides a compressed image with high quality. Inorder to improve the compression ratio vector quantization for color images is proposed. This provides good quality images with high PSNR values. The algorithm uses low memory requirement.
Keywords: PCA, non uniform quantizers.compression ratio,vector quantization, PSNR values.