Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces

Abstract

This paper consists of a lossy image compression algorithm dedicated to the medical images doing comparison of RGB and YCbCr color space. Several lossy/lossless transform coding techniques are used for medical image compression. Discrete Wavelet Transform (DWT) is one such widely used technique. After a preprocessing step (remove the mean and RGB to YCbCr transformation), the DWT is applied and followed by the bisection method including thresholding, the quantization, dequantization, the Inverse Discrete Wavelet Transform (IDWT), YCbCr to RGB transform of mean recovering. To obtain the best compression ratio (CR), the next step encoding algorithm is used for compressing the input medical image into three matrices and forward to DWT block a corresponding containing the maximum possible of run of zeros at its end. The last step decoding algorithm is used to decompress the image using IDWT that is applied to get three matrices of medical image.

Share and Cite:

A. Jayprkash and R. Vijay, "Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces," Journal of Signal and Information Processing, Vol. 4 No. 4, 2013, pp. 364-369. doi: 10.4236/jsip.2013.44046.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] F. Kammoun, W. Fourati and M. S. Bouhlel, “Comparative Survey of the DCT and the Wavelet Transforms for Image Compression,” Journal of Testing and Evaluation, Vol. 34, No. 6, 2006, Article ID: JTE100086.
[2] Y. C. Li, Q. Yang and R. H. Jiao, “Image Compression Scheme Based on Curvelet Transform and Support Vector Machine,” Expert Systems with Applications, Vol. 37, No. 4, 2010, pp. 3063-3069. http://dx.doi.org/10.1016/j.eswa.2009.09.024
[3] F. Douak, R. Benzid and N. Benoudjit, “Color Image Compression Algorithm Based on the DCT Transform Combined to an Adaptive Block Scanning,” International Journal of Electronics and Communications (AEU), Vol. 65, No. 1, 2011, pp. 16-26.
[4] N. Sriraam and R. Shyamsunder, “3-D Medical Image Compression Using 3-D Wavelet Coders,” Digital Signal Processing, Vol. 21, No. 1, 2011, pp. 100-109. http://dx.doi.org/10.1016/j.dsp.2010.06.002
[5] K. M. M. Prabhu, K. Sridhar, M. Mischi and H. N. Bharath, “3-D Warped Discrete Cosine Transform for MRI Image Compression,” Biomedical Signal Processing and Control, 2012, In Press.
[6] R. Shyam Sunde, C. Eswaran and N. Sriraam, “Medical Image Compression Using 3-D Hartley Transform,” Computers in Biology and Medicine, Vol. 36, No. 9, 2006, pp. 958-973. http://dx.doi.org/10.1016/j.compbiomed.2005.04.005
[7] M. Boixa and B. Canto, “Wavelet Transform Application to the Compression of Images,” Mathematical and Computer Modeling, Vol. 52, No. 7-8, 2010, pp. 1265-1270.
http://dx.doi.org/10.1016/j.mcm.2010.02.019
[8] V. Bruni and D. Vitulano, “Combined Image Compression and Denoising Using Wavelets,” Signal Processing: Image Communication, Vol. 22, No. 1, 2007, pp. 86-101.
http://dx.doi.org/10.1016/j.image.2006.11.006
[9] A. Graps, “An Introduction to Wavelets,” IEEE Computational Science and Engineering, Vol. 2, No. 2, 1995, pp. 50-61. http://dx.doi.org/10.1109/99.388960
[10] C. Lin, “Face Detection in Complicated Backgrounds and Different Illumination Conditions by Using YCbCr Color Space and Neural Network,” Pattern Recognition Letters, Vol. 28, No. 16, 2007, pp. 2190-2200. http://dx.doi.org/10.1016/j.patrec.2007.07.003
[11] B. Kang, C. Jeon, D. K. Han and H. Ko, “Adaptive Height-Modified Histogram Equalization and Chroma Correction in YCbCr Color Space for Fast Backlight Image Compensation,” Image and Vision Computing, Vol. 29, No. 8, 2011, pp. 557-568. http://dx.doi.org/10.1016/j.imavis.2011.06.001
[12] J. M. Chaves-Gonzalez, M. A. Vega-Rodriguez, J. A. Gomez-Pulido and J. M. Sanchez-Perez, “Detecting Skin in Face Recognition Systems: A Colour Spaces Study,” Digital Signal Processing, Vol. 20, No. 3, 2010, pp. 806- 823. http://dx.doi.org/10.1016/j.dsp.2009.10.008
[13] S. Kumar Singh and S. Kumar, “Novel Adaptive Color Space Transform and Application to Image Compression,” Signal Processing: Image Communication, Vol. 26, No. 10, 2011, pp. 662-672. http://dx.doi.org/10.1016/j.image.2011.08.001
[14] J. P. Agrawal and R. Vijay, “Wavelet Compression of CT Medical Images,” IJSRET, Vol. 1, No. 3, 2012, pp. 45-51.
[15] J. D. Allen, “An Approach to Fast Transform Coding in Software Signal Processing,” Image Communication, Vol. 8, No. 1, 1996, pp. 3-11. http://dx.doi.org/10.1016/0923-5965(94)00047-6

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.