S S ParthaSarathy

Work place: Department of Electrical and Electronics Engineering, PESCE, Mandya

E-mail: vsarathypartha@yahoo.com


Research Interests: Engineering, Image Processing, Image Manipulation, Image Compression, Computational Engineering


Dr. S S parthasarathy completed B.E from NIE, Mysore and M-Tech form IIT Kharagpur. He has completed Ph.D from IIT Madras, Chennai. He is currently working as professor in the Dept. of Electrical and Electronics at PES college of Engineering an autonomous institution, Mandya, Karanataka, India. He has published more than 30 research publications in various National, International Conference proceedings and journals. He is a fellow of Institute of Engineers, member of ISTE and served as BOE chairman for electrical and electronics department for VTU. Presently BOE and BOS member for several autonomous Institutions. His area of research includes advanced control engineering and image processing.

Author Articles
Analysis and Estimation of Noise in Embedded Medical Images

By C Nagaraju S S ParthaSarathy

DOI: https://doi.org/10.5815/ijigsp.2015.03.07, Pub. Date: 8 Feb. 2015

Patient information is embedded inside the medical images for the storage or transmission, or healthcare applications. In medical image processing, various types of noises corrupt the image quality. There is a need of measure specific noise for a particular image is required for the evaluation of robustness for embedding techniques used for hiding patient information in medical images. It is very important to obtain precise images to facilitate accurate analysis and estimation of noise in embedded medical image. The current work is focused towards studying the effect of specific noise which affect particular medical image. The strength of the medical image is tested by introducing several attacks to the embedded medical images. The statistical quantity measures like peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and normalized root mean square error (NRMSE) are employed to measure the quality of the output medical image.

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