Image compression using multiwavelet transform for medical image

This paper analysis the performance of multiwavelet transform on compression of medical images. Geronimo-Hardin-Massopust (GHM), Chui Lian (CL) and Hardin Marasovich (HM) are subjected to multiwavelet transform in image transformation stage. Set partitioned in Hierarchical Tree (SPIHT) is used as a common platform for encoding the transformed coefficients. Peak Signal Noise Ratio (PSNR), Mean Square Error (MSE) and Compression Ratio (CR) are used as a metrics to perform the analysis. For this proposed work we have used CT Scan Brain image of Hemorrhage images.