Performance analysis of SPIHT codec on medical images using DWT and IWT - Revathi, M; Shenbagavalli, R (International Journal of Computer Sciences and Engineering, 2025)
Image compression in medical image processing is a most significant technique which reduces the burden of storage and transmission time over the network with less degradation in the visual quality and without information loss. Image compression techniques are used to reduce the volume of data for effective storage and transmission. They are classified into lossy compression and lossless compression. In this work, Magnetic Resonance Imaging (MRI) of brain and Computer Tomography (CT) of lung images are used for analyzing compression. The images are compressed using Discrete Wavelet Transform (DWT)-Set Partitioning In Hierarchical Trees (SPIHT) and Integer Wavelet Transform (IWT)-SPIHT with three wavelets such as Haar, Sym4 and Coif1. DWT is used for lossy compression and IWT is used for lossless compression of images. The performance metrics such as Peak signal-to-noise ratio (PSNR), Bit Per Pixel (BPP) and Mean square error (MSE) are measured for lung and brain images. The comparative analyses for SPIHT with DWT and IWT are calculated based on the performance of wavelet. The dataset has been collected from various scan centers