Lakshminarayana. M

Work place: Dept. of ECE, Visvesvaraya Technological University, Belgaum, Karnataka, India



Research Interests: Multimedia Information System, Image Processing, Image Manipulation, Image Compression, Embedded System, Computer systems and computational processes


Lakshminarayana. M received the B.E. degree in Medical Electronics from Dr. AIT, Bangalore in 2005 and the M. Tech degree in Electronics from Sir. MVIT, Bangalore in 2007 under Visvesvaraya Technological University, Belgaum, where he is currently working towards the Ph.D. degree under VTU in the field of Multimedia Communication applications. He is the member of Professional bodies IEEE, MISTE, IAENG. His current research interests include the areas of Multimedia communication, Image and video processing and DSP applications in embedded system design.

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

By Lakshminarayana. M Mrinal Sarvagya

DOI:, 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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