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

Authors: Kuldeep Yadav; Avi Srivastava; Ankush Mittal; M.A. Ansari

Addresses: 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

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.

Keywords: basis pursuit algorithm; compressed domain image retrieval; compressive sensing; medical imaging; DCT; discrete cosine transform; content based image retrieval; texture based image retrieval; compressive sampling; acquisition speed; image quality; medical images.

DOI: 10.1504/IJBRA.2014.059519

International Journal of Bioinformatics Research and Applications, 2014 Vol.10 No.2, pp.129 - 144

Available online: 25 Feb 2014 *

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