Compression is useful in reduction of the cost of transmission bandwidth and storage of larger size images. One of advanced form of compression is based on wavelet compression. DWT can be used to reduce the image size without losing much of the resolutions computed. It reduces the amount of memory required to represent given image [1]. This paper covers a review of the fundamentals of image compression based on wavelet and also presents wavelet based low bit rate video coding technique. Wavelet based image compression has been illustrated using DSP Processor platform. The implementation of DWT compression algorithm using embedded approach has been tried with DSP processor TMS320C6713. DWT algorithm is implemented using C language. The Code Composer Studio (CCS) software is used to simulate the code written in C language to successful display the compression result on TI's digital signal processing board TMS320C6713. DSP simulation results are verified using MATLAB simulation results. Compression ratio for the image compressed by DSP simulation is obtained as 1. 0124. Compression ratio by MATLAB simulation is obtained same as 1. 0124. This work shows that average simulation time of the system is 21 milliseconds and memory used is 2. 5Kbyte. The coefficients of compressed image which are the results of MATLAB software and C language using Code Composer Studio (CCS), IDE Environment are closely matched.

1. Gerlind Ploanka, Stefanie Tenorth and Daniela Rosca "A New Hybrid Method for Image Approximation Using the Easy Path Wavelet Transform" IEEE Trans. Image Processing, vol. 20, No. 2, feb 2011
2. E. Elharar, Adrian Stern and Ofer Hadar "A Hybrid Compression Method for Integral Images Using Discrete Wavelet Transform and Discrete Cosine Transform" IEEE journal vol. 3, No. 3, September 2009
3. Jin Li and C. -C. Jay Kuo "Image Compression with a Hybrid Wavelet-Fractal Coder", IEEE transactions on image processing, vol. 8, No. 6, june 1999
4. Diego Santa Cruz and Touraelj Ebrahimi, "An Analytical Study Of JPEG 2000 Functionalities", IEEE 2000.
5. Robi Polikar, The Wavelet Tutorial http://engineering. rowan. edu/~polikar/WAVELETS/Wttutorial. html
6. Saha, Subhasis. Image Compression from DCT to Wavelets : A Review http://www. acm. org/crossroads/xrds6-3/sahaimgcoding. html
7. Jayashree Karlekar & U. B. Desai, "Content Based Very Low Bit Rate Video Coding Using Wavelet Transform", IEEE transaction on image processing, vol. 9, No. 7, june 1999.
8. Berkeley Design Technology, Inc. , "Buyer's Guide to DSP Processors," Berkeley Design Technology, Inc. , 1994, 1995, 1997, 1999.
9. Sonja Grgic, Mislav Grgic, Member, IEEE, and Branka Zovko-Cihlar, Member, IEEE, "Performance Analysis of Image Compression Using Wavelets", vol. 48, No. 3, june 2001
10. Yogendra Kumar Jain & Sanjeev Jain, "Performance Evaluation of Wavelets for Image Compression". International Journal of soft Computing2 (1):1104-112, 2006
11. C. S. Burrus, R. A. Gopinath and H. Guo , Introduction to Wavelets and Wavelet Transforms, Prentice Hall, 1998.
13. A. Graps, 'An Introduction to Wavelets', IEEE Computational Science and Engineering, Vol. 2, No. 2 Summer 1995.
14. Hubbard, Barbara Burke. The World According to Wavelets. A. K Peters Ltd, 1995.
15. Rulph chassaing,'Digital Signal Processing and Application' Willey Interscience , 2005
16. K. S. Thyagrajan,'Still Image and Video Compression with MATLAB' Willey Interscience , 2011

Discrete Wavelet Transform (dwt) Dsp Processor Code Composer Studio (ccs) Software Matlab Simulation Low Bit Rate Video Coding Compression Ratio Ide Environment