PATEL AMRUTBHAI PATEL, Dr. Vijay K. Patel, Prof. Yogesh B. Patel


This research paper presents a combined approach to Lossy image compression algorithm, based on wavelet transform, Global thresholding, Vector quantization and Source coding like Huffman coding and LZW coding. In this image compression algorithm, discrete wavelet transform (DWT) is applied on input image, which decomposes the input image into a sequence of wavelet coefficients. Global thresholding is used to modify the wavelet coefficients image. Resultant coefficients after thresholding are quantized using vector quantization technique and later, VQ indices are coded using LZW coding to increase the compression ratio. The main objective of the present study is to obtain better quality of decompressed images even at very low bit rates and to reduce the size of the data as well as processing and transmission time. Considerable efforts have been made to design image compression methods. Experimental results are measured in terms of Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index Measurement (SSIM) for image quality and its performance has been compared to the already existing methods. The proposed method of lossy image compression shows better image quality in terms of PSNR at the same compression ratio as compared to other image compression techniques.


Discrete wavelet transform (DWT); Vector quantization (VQ); Peak signal to noise ratio (PSNR); Mean square error (MSE).

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Amrutbhai N Patel, Dr. D. J. Shah, “SSIM based image quality assessment for vector quantization based lossy image compression using LZW coding”, University Journal of Research (UJR) Volume 1, Issue 1, Pg. 16-29, August-2015.

Amrutbhai N Patel, Dr. D. J. Shah, “Structural Similarity Index Measurement (SSIM) Based Performance Analysis of Wavelet Families for Image Compression”, International Journal of Emerging Technologies and Applications in Engineering, Technology and Sciences (IJETAETS), ISSN: 0974 3588, Pg. 104-114, December-2014.

Zhou Wang, Alan Conrad Bovik, Hamid Rahim Sheikh, “Image Quality Assessment: From Error Visibility to Structural Similarity”, IEEE transactions on image processing, volume. 13, no. 4, April 2004.

Nandi, U., Mandal, J.K., "A Compression Technique Based on Optimality of LZW Code (OLZW)," Computer and Communication Technology (ICCCT), 2012 Third International Conference on, vol., no., pp.166, 170, 23-25 November. 2012.

Srinivasan, K, K Porkumaran, and G Sainarayanan. "An approach of wavelet transform-based human pose models for indoor video applications", The Imaging Science Journal, 2012.

.Hage, Pankaj S., Sanjay B. Pokle, and Venkateshwarlu Gudur. "Discrete wavelet transform based video signal processing", 2014 International Conference on Advances in Communication and Computing Technologies (ICACACT 2014), 2014.

Truong Q. Nguyen. "Motion wavelet difference reduction (MWDR) video codec", International Conference on Image Processing ICIP 04, 2004.

A., "Multiresolution Analysis Based Effective Diagnosis of Induction Motors", American Journal of Applied Sciences, 2012.

Vimala, S. "Techniques for generating initial codebook for Vector Quantization",3rd International Conference on Electronics Computer Technology, 2011.

Kalaivani, K., C. Thirumaraiselvi, and R. Sudhakar. "An effective way of image compression using DWT and SOM based vector quantization", IEEE International Conference on Computational Intelligence and Computing Research, 2013.

Fatone, Lorella, Maria Cristina Recchioni, and Francesco Zirilli. "Wavelet Bases Made of Piecewise Polynomial Functions: Theory and Applications", Applied Mathematics, 2011.

A.Z. Averbuch, F. Meyer, J.-O. Stromberg, R. Coifman, A. Vassiliou. "Low bit-rate efficient compression for seismic data", IEEE Transactions on Image Processing, 2001.

Devcic, John. "UDVA: Understanding Digital Video Architecture: MPEG-2, DivX, AVCHD: these are just a few of the con", Video maker, April 2007.



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