TY  - JOUR
AU  - Tamilarasi, M. 
AU  - Palanisamy, V. 
PY  - 2011
TI  - Medical Image Compression Using Fuzzy C-Means Based Contourlet Transform
JF  - Journal of Computer Science
VL  - 7
IS  - 9
DO  - 10.3844/jcssp.2011.1386.1392
UR  - https://thescipub.com/abstract/jcssp.2011.1386.1392
AB  - Problem statement: To meet the demand for high speed transmission of image in efficient
image storage and remote medical treatment, the efficient image compression is essential. The
contourlet transform along with wavelet theory has great potential in medical image compression.
Approach: The significant portion of the medical image applied with Fuzzy C-means based
contourlet transform. DWT applied to the rest of the image. Finally modified EZW of six symbols
differing from normal EZW was applied to the whole image. This technique increases PSNR and
gives better compression ratio. Results: The MATLAB simulation showed that the method of
separate transforms to the two regions proves better results compared to the ordinary way of applying
only single transforms to the whole image. The results revealed that proposed algorithm was simple
and computationally fewer complexes based on embedded block coding with coefficient truncation.
Conclusion: The compression of the proposed algorithm is superior to EZW, SPIHT. Our new
method of compression algorithm can be used to improve the performance of Compression Ratio
(CR) and Peak Signal to Noise Ratio (PSNR). In future this study can be extended to real time
applications for video compression in medical images.