Medical image compression is an important area of research which aims at producing algorithms that reduce file size and at the same time maintain relevant diagnostic information. The main focus of this paper is to analyze techniques and find a compression scheme that can compress medical images quickly and reduce compression rate while maintaining a good level of visual quality. In most cases physicians may not afford any deficiency in diagnostically important regions of images; called regions of interest (ROIs). In order to bring that, a high compression ratio with good quality in the ROI is thus needed. Embedded zero tree wavelet (EZW) coding, is a very effective and computationally simple technique for image compression Moreover, they present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than their previously reported extension of EZW that surpassed the performance of the original EZW.

Full text: IJEIR_1598_Final.pdf