Texture-based medical image retrieval in compressed domain using compressive sensing

Authors:
Kuldeep Yadav;Avi Srivastava;Ankush Mittal;M. A. Ansari
Affiliations:
Computer Science Department, College of Engineering Roorkee, Roorkee, India;Computer Science Department, College of Engineering Roorkee, Roorkee, India;Computer Science Department, Graphic Era University, Dehradun, India;Department of Electrical Engineering, School of Engineering, Gautam Buddha University GBU, Greater Noida, India
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2014

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Abstract

Content-based image retrieval has gained considerable attention in today's scenario as a useful tool in many applications; texture is one of them. In this paper, we focus on texture-based image retrieval in compressed domain using compressive sensing with the help of DC coefficients. Medical imaging is one of the fields which have been affected most, as there had been huge size of image database and getting out the concerned image had been a daunting task. Considering this, in this paper we propose a new model of image retrieval process using compressive sampling, since it allows accurate recovery of image from far fewer samples of unknowns and it does not require a close relation of matching between sampling pattern and characteristic image structure with increase acquisition speed and enhanced image quality.