Science Journal of Education
Volume 3, Issue 4-1, August 2015, Pages: 17-20
Received: May 16, 2015;
Accepted: May 18, 2015;
Published: Jun. 1, 2015
Views 5052 Downloads 137
L. Nirmal Jega Selvi, Department of CSE, St. Joseph College of Engineering and Technology, Dar es Salaam, United Republic of Tanzania
Lossless image compression has one of its important applications in the field of medical images. Efficient storage, transmission, management and retrieval of the huge data produced by the medical images have nowadays become very much complex. The solution to this complex problem lies in the lossless compression of the medical images. The medical data is compressed in such a way so that no medical information is lost. The super spatial structure prediction algorithm is used to find the optimal prediction of structured components in an image. The block matching is achieved using inverse diamond search algorithm. And finally LZ8 algorithm is applied to achieve the higher compression ratio of the medical images.
L. Nirmal Jega Selvi,
Medical Image Compression Using DEFLATE Algorithm, Science Journal of Education. Special Issue: Science Learning in Higher Education.
Vol. 3, No. 4-1,
2015, pp. 17-20.
X. Wu and N. Memon, ”Context-based adaptive lossless image coding”, IEEE Trans. Commun, vol 45.no.4,pp 437-444, Apr 1997.
Abdesh Singla, Kulbhushan Singla. A, “New lossless compression scheme for medical images”, EXCEL International Journal of Multidisciplinary Management Studies (EIJMMS) Vol.3 (7) July (2013).
M. Moorthi, Dr. Amudha, “A near lossless compression method for medical images”, IEEE-International Conference on Advances in Engineering, Science and Management (ICAESM-2012) March30, 2012.
Smitha Joyce Pinto, Jayanand P Gawande, “Performance analysis of medical image compression techniques”, IEEE Transaction on image processing, (2012).
S. Zhu and K.K. Ma, ‘A New diamond search algorithm for fast block matching motion estimation”, IEEE Trans. Image Process.,9: 287-290,2000.
L. M. Po, C.W. Ting, K. M. Wong and K. H. Ng,” Novel point-oriented inner searches for fast block motion estimation”, IEEE Trans. Multimedia,9:9-15,2007.
P. Franti,” A Fast and Efficient Compression Method for Binary Images”,1993.
B .Brindha, G. Raghuraman, “Region based lossless compression for digital images in telemedicine application”, International conference on Communication and Signal Processing, April (2013).
P. Sudha , “Image compression with scalable ROI using adaptive huffman coding”, IJCSMC, Vol. 2, Issue.4 (2012).
R. Rajeshwari and R. Rajesh, “WBMP Compression”, International journal of Wisdom Based Computing, vol.1, No.2, 2011.