Authors: P. Eben Sophia; J. Anitha
Addresses: ECE, Karpagam College of Engineering, Coimbatore, 641032, India ' Electronics and Communication Engineering, Karunya University, Coimbatore, 641114, India
Abstract: With the aim of improving the compression performance using contourlet transform, singular value decomposition (SVD) of intermediate sub-bands has been experimented. In this way, the size of contourlet transform sub-bands can be efficiently reduced to induce compression. This novel lossy compression technique enhances the compression performance of contourlet transform and produces good quality image even at lower bit rates. In addition to SVD, normalisation and prediction of decomposed sub band coefficients also improve the compression performance. The method was tested using medical magnetic resonance imaging (MRI) and computed tomography (CT) imaging modalities. The statistical results confirm the efficiency of the proposed method in terms of compression ratio (CR), peak signal to noise ratio (PSNR) and bits per pixel (BPP). This method produces good compression with approximately 47 dB PSNR at bit rate as low as 0.1 BPP. This is suggested good for medical image communication and storage applications such as picture archiving communication system (PACS), radiology information system (RIS), etc., and also helps in easy search and retrieval process.
Keywords: contourlet transform; singular value decomposition; SVD; prediction; lossy compression; arithmetic coding; medical MRI and CT images etc.
International Journal of Advanced Intelligence Paradigms, 2019 Vol.14 No.1/2, pp.107 - 121
Received: 18 Jul 2016
Accepted: 21 Nov 2016
Published online: 14 Oct 2019 *