Enhanced method of using contourlet transform for medical image compression
by P. Eben Sophia; J. Anitha
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 14, No. 1/2, 2019

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.

Online publication date: Mon, 14-Oct-2019

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