The Medical Image Compression with Embedded Zerotree Wavelet

The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing and high definition television, (HDTV) has increased the need of effective image processing. While processing any data, it requires large memory space for storage, which ultimately increases the transmission time. In order to save memory space and speed up the rate of transmission of data over networks, data compression is essential. Technically all image data Compressed into two groups as lossless and lossy. Some information is lost in the lossy compression, especially for radiological images. To minimize the effect of data loss on the diagnostic features of the images a new algorithm can be designed. Wavelet transform (WT) constitute a new compression technology that has been used in natural and medical images. In this study, the embedded zerotree wavelet algorithm (EZW) is used for image coding. It is designed to optimize the combination of zerotree coding and Huffman coding. It is shown that the multi-iteration algorithm and particularly the two iteration EZW for a given image quality produce lower bit rate. It is applied for medical images and here, the thorax radiology is chosen as a sample image and the good performance is codified. This compression technique can be used for Office automation, Bio-medical, Remote Sensing, Criminology, Astronomy and space applications, Information technology and Military applications.