Texture-based medical image retrieval in compressed domain using compressive sensing. (1st January 2014)

• Record Type: Journal Article
• Authors: Yadav, Kuldeep; Srivastava, Avi; Mittal, Ankush; Ansari, M.A.
• Is Part Of: International journal of bioinformatics research and applications. Volume 10:Number 2(2014)
• Page Start: 129
• Page End: 144
• Publication Date: 2014-01-01
• Subjects: Basis Pursuit algorithm -- compressed domain image retrieval -- compressive sensing -- medical imaging -- DCT -- discrete cosine transform; Bioinformatics -- Periodicals; 570.285
• Languages: English
• ISSNs: 1744-5485

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.