Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression q J. Jyotheswar, Sudipta Mahapatra * Department of Electronics and Electrical Communication Engineering, IIT Kharagpur, Kharagpur 721 302, West Bengal, India Received 16 May 2006; received in revised form 1 November 2006; accepted 1 November 2006 Available online 19 January 2007 Abstract In this paper, we present an implementation of the image compression technique set partitioning in hierarchical trees (SPIHT) in programmable hardware. The lifting based Discrete Wavelet Transform (DWT) architecture has been selected for exploiting the correlation among the image pixels. In addition, we provide a study on what storage elements are required for the wavelet coefficients. A modified SPIHT (Set Partitioning in Hierarchical Trees) algorithm is presented for encoding the wavelet coefficients. The modifications include a simplification of coefficient scanning process, use of a 1-D addressing method instead of the original 2-D arrangement for wavelet coefficients and a fixed memory allocation for the data lists instead of the dynamic allocation required in the original SPIHT. The proposed algorithm has been illus- trated on both the 2-D Lena image and a 3-D MRI data set and is found to achieve appreciable compression with a high peak-signal-to-noise ratio (PSNR). Ó 2006 Elsevier B.V. All rights reserved. Keywords: Medical image compression; Wavelet transform; SPIHT; Lifting scheme; PSNR 1. Introduction Lossless image compression techniques find applications in fields such as medical imaging, pres- ervation of artwork, remote sensing etc. [1]. In addi- tion to being lossless, tools for compressing and decompressing medical images need to be imple- mented with high speed for accurate and timely diagnosis. Compressing an image set with multiple slices is very important in medical imaging as the most commonly used digital modalities, including Magnetic Resonance (MR), Computed Tomogra- phy (CT), Positron Emission Tomography (PET), and Single Photon Emission Computed Tomogra- phy (SPECT), generate multiple slices in a single examination [2,3,9]. One slice is normally a cross section of the body part. Multiple slices generated in this way are normally anatomically or physiolog- ically correlated to each other. In other words, there are some image structural similarities between adja- cent slices. Although it is possible to compress an image set slice by slice, more efficient compression 1383-7621/$ - see front matter Ó 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.sysarc.2006.11.009 q This work was supported in part by the SERC Fast Track Scheme of the Department of Science and Technology, Govt. of India. * Corresponding author. Tel.: +91 3222283560; fax: +91 3222282264. E-mail addresses: Jyothish.J@gmail.com (J. Jyotheswar), Sudipta@ece.iitkgp.ernet.in (S. Mahapatra). Journal of Systems Architecture 53 (2007) 369–378 www.elsevier.com/locate/sysarc