IJSER Home >> Journal >> IJSER
International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 8    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 8,August 2012
Image Compression Hybrid using DCT , DWT , Huffman
Full Text(PDF, )  PP.911-914  
Harjeetpal Singh , Sakshi Rana
DCT (discrete cosine transform), DWT (discrete wavelet transform), MSE (mean square error), PSNR (peak signal to noise ratio)
Image compression literally means reducing the size of graphics file, without compromising on its quality. Depending on whether the reconstructed image has to be exactly same as the original or some unidentified loss may be incurred, two techniques for compression exist. Image compression is an essential technology in multimedia and digital communication fields. Ideally, an image compression technique removes redundant and/or irrelevant information, and efficiently encodes what remains. Practically, it is often necessary to throw away both on redundant information and relevant information to achieve the required compression. in either case, the trick is finding methods that allow important information to be efficiently extracted and represented. Most of the existing image coding algorithm is based on the correlation between adjacent pixels and therefore the compression ratio is not high. Fractal coding is a potential image compression method, which is based on the ground breaking work of Barnsley and was developed to a usable state by Jacquin.Its essence is that correlation not only exists in adjacent pixels within a local region, but also in different regions and local regions with global regions. The fractal-based schemes exploit the self-similarities that are inherent in many real world images for the purpose of encoding an image as a collection of transformations. Here in this hybrid model we are going to proposed a Nobel technique which is the combination of several compression techniques. This paper presents DWT and DCT implementation because these are the lossy techniques and in the last we introduce Huffman decoding technique which is lossless. At the last we implement lossless technique so our PSNR and MSE will go better than the old algorithms and due to DWT and DCT we will get good level of compression.
[1] M.Rabbani and P. Jones, “Digital image compression techniques,SPIE Opt. Eng. Press,, Bellingham, Washington, Tech. Rep., 1991

[2] G. Kuduvalli and R. Rangayyan, “Performance analysis of reversibl Image compression techniques for high resolution digital Teleradiology,” in IEEE Trans. Med. Imaging, vol. 11, Sept. 1992

[3] J.M.Shapiro, “Embedded image coding using zerotrees of wavelet Coefficients,” in Special Issue on Wavelet And Signal Processing,vol.41.no.12.IEEE Trans.Signal Processing, Dec1993.

[4] Said and W. A. Pearlman, “An image multiresolution representation for lossless and lossy compression,” in IEEE Transactions On Image Processing, vol. 5, no. 9, September 1996.

[5] X. Li, Y. Shen, and J. Ma, “An efficient medical image compression,,”in Engineering In Medicine And Biology 27th Annual Conference,Shangai,China, September 1-4 2005 IEEE

[6] Ali Al-Fayadh, Abir Jaafar Hussain, Paulo Lisboa, and Dhiya Al-Jumeily “An Adaptive Hybrid Classified Vector Quantisation and Its Application to Image Compression” 2008 IEEE

[7] Zhang Shi-qiang,Zhang Shu-fang, Wang Xin-nian, Wang Yan “ The Image Compression Method Based on Adaptive Segment and Adaptive Quantified” 2008 IEEE

[8] Sunil Bhooshan , Shipra Sharma “ An Efficient and Selective Image Compression Scheme using Huffman and Adaptive Interpolation” 2009 IEEE

[9] Ying Xie , Xiaojun Jing ,Songlin Sun ,Linbi Hong “ A Fast And Low Complicated Image Compression Algorithm For Predictor For JPEG-LS” 2009 IEEE

[10] Chong Fu ,Zhi-Liang Zhu “ A DCT-Based Fractal Image Compression Method” 2009 IEEE

[11] Chunlei Jiang, Shuxin Yin “A Hybrid Image Compression Based on Human Visual System” 2010 IEEE

[12] Suchitra Shrestha and Khan Wahid “ Hybrid DWT-DCT Algorithm for Bio-Medical Image And Vedio Compression Applications”2010 IEEE.

[13] F.M. Bayer and R J Cintra “ Image Compression Via a Fast DCT Approximation” 2010 IEEE

[14] LIU Wei “ Research on Image Compression Algorithm Based on SPHIT” 2010 IEEE

[15] Mamta Sharma, S.L. Bawa D.A.V. college, “Compression Using Huffman Coding” may 2010 IJCSNS

[16] Aree Ali Mohammed and Jamal Ali Hussian “Hybrid Transform Coding Scheme for Medical Image Application” 2011 IEEE

[17] T. Goto and Y. Kato “ Compression Artifect Reduction based on Total Variation Regularization Method for MPEG-2” 2011 IEEE

[18] Amar Agoun “ Compression of 3D Intergral Images using 3D wavelet Transform” 2011 IEEE.

[19] XiHong ZHOU “ Research on DCT Based Image Compression Quality”2011 IEEE

[20] Said and W. A. Pearlman, “An image multiresolution representationfor lossless and lossy compression,” to appear in theIEEE Transactions on Image Processing

Untitled Page