Lossless Hybrid Coding technique based on Quasi Fractal & Oscillation Concept Method for Medical Image Compression
The Image compression is the most important entity in various fields. Image compression plays vital role in many applications. Out of which biomedical is one of the challenging applications. In medical research, everyday there is fast development and advancement. Medical researchers are thinking about digital storage of data hence medical image compression has a crucial role in hospitals. Here Morphological filter & adaptive threshold are used for refinement and used Quasi Fractal & Oscillation concept for developing new hybrid algorithm. Oscillation concept is lossy image compression technique hence applied on Non-ROI. Quasi fractal is lossless image compression technique applied on ROI. The experimental results shows that better CR with acceptable PSNR has been achieved using hybrid technique based on Morphological band pass filter and Adaptive thresholding for ROI. Here, innovative hybrid technique gives the CR 24.61 which improves a lot than hybrid method using BTC-SPIHT is 5.65. Especially PSNR is also retained and bit improved i.e. 33.51. This hybrid technique gives better quality of an image.
Korakot Prachumrak, Akira Hiramatsu, Takayasu Fuchida, Hitofumi Nakamura and Sadayuki Murashima, Lossless Fractal Image Coding, 4th EURASIP Conference Focused on Video / Image Processing and Multimedia Communications. 2-5 July 2003.
S. Bhavani & Dr. K. Thanushkodi, A New Algorithm for Fractal Coding Using Self Organizing Map, Journal of Computer Science, 841- 845, 2012.
Ju Cheng Yang, Dong Sun Park, Detecting Region-of-Interest (ROI) in Digital Mammogram by using Morphological Bandpass Filter, IEEE ,2004
Francesco G.B. De Natale, Giulia Boato, Detecting Morphological Filtering of Binary Images, IEEE Transaction, 2016.
Rahul Sharma, Chandrashekhar Kamargaonkar and Dr. Monisha Sharma, Hybrid Medical Image Compression: Survey, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 5, Issue 4, April 2016.
Alyaa H., Medical Image Data Compression Using Hybrid Methods, ARPN Journal of Engineering and Applied Sciences, VOL. 13, NO. 5, March 2018.
Benamrane Nacera Bentorki Soumia, A Hybrid Scheme Coding Using SPIHT and Fractal for Mammography Image Compression, 15th International Conference on Information Visualization, IEEE Xplore, 2011.
Nehal Markandeya, Sonali Patil, Digital Image Compression Hybrid Technique Based on Block Truncation Coding and Discrete Cosine Transform, International Conference on Trends in Electronics and Informatics, ICEI 2017.
Harjeetpal Singh, Sakshi Rana, Image Compression Hybrid using DCT, DWT, Huffman, International Journal of Scientific & Engineering Research (IJSER), Volume 3, Issue 8, August-2012.
Seddeq E. Ghrare & Ahmed R. Khobaiz, Digital Image Compression Using Block Truncation Coding and Walsh Hadamard Transform Hybrid Technique, IEEE 2014 International Conference on Computer, Communication, and Control Technology (I4CT 2014), September 2-4, 2014.
G. Soundarya, Comparison of Hybrid Codes for MRI Brain Image Compression, Research Journal of Applied Sciences, Engineering and Technology 4(24), 2012.
Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Pearson, Education, Inc., Second Edition, 2004.
Rafael C. Gonzalez, Richard E. Woods, Steven Eddins, Digital image Processing using MATLAB’, Pearson Education, Inc. ,2004.
R.N. Chaudhary, Waves and Oscillations, New Edge International Publishers
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