Mrinal Sarvagya

Work place: REVA University, Bangalore, Karnataka, India

E-mail: mrinalsarvagya@gmail.com

Website:

Research Interests: Computer Networks, Computer systems and computational processes, Computational Science and Engineering

Biography

Dr. Mrinal Sarvagya received the B.E. degree from Govt. Engg. college of Ujjain in 1993, The M.E. degree from the S.G.S.I.T.S. Indore in 1999 and the Ph.D. degree in Electronics and Communication Engineering from IIT Kharagpur in 2010. She received the best thesis award from IIT Kharagpur in the year 2009 for her thesis titled “QoS based packet scheduling and resource allocation schemes for WCDMA UMTS”. She is the member of Professional bodies WIE, IEEE. She held the position of Member, Board of studies, G. H. Raisoni College of Engineering Nagpur, Member, Board of studies, VNSIT Mumbai, Member, board of studies, SGSITS Indore, Member, DBUGC Nitte Meenakshi Institute of Technology, Bangalore. She is currently working professor and HOD (PG-ECE) REVA University, Bangalore. Her area of research are Ad-hoc wireless networks, wireless communication, and channel equalization in OFDM-IDMA, SCM receivers, and cognitive Radio networks.

Author Articles
RM2IC: Performance Analysis of Region based Mixed-mode Medical Image Compression

By Lakshminarayana. M Mrinal Sarvagya

DOI: https://doi.org/10.5815/ijigsp.2017.10.02, Pub. Date: 8 Oct. 2017

The medical data science has been changing from conventional analog to more powerful digital imaging systems for some time. These imagining systems produced images in digital form. As digital technology evolves and exceeds the capability of analog imaging devices, so too does the expansion in the range of applications for image guided surgical and diagnostic systems. The optimization of bandwidth and storage are the major issues in image processing technology. The Compressive Sensing (CS) algorithm can become prominent tool for these issues because it can sample the signal with much lesser sample rate than twice of the maximum frequency of the signal and reconstruct the signal similar to the original signal. This paper, presents a novel scheme Region based Mixed-mode Medical Image Compression (RM2IC). Here, the region of interest is compressed with lossless hybrid compression methods and the non-region of interest is com-pressed with lossy hybrid CS algorithm. RM2IC is compared with different existing hybrid compression methods and it outperforms better visual perceptional quality of reconstructed image and reduces the compression rate. The performance analysis is done based on PSNR, MSE and compression ratio. 

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