Comparative analysis between discrete cosine transform and wavelet transform techniques for medical image compression

Abstract

Image compression reduces irrelevant and redundancy of the image data in order to be able to store or transmits data in an efficient form. Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages. Medical image compression plays a key role as hospitals move towards filmless imaging and completely digital. Image compression will allow Picture Archiving and Communication Systems (PACS) to reduce the file sizes on their storage requirements while maintaining relevant diagnostic information. Teleradiology sites benefit since reduced image file sizes yield reduced transmission times. Even as the capacity of storage media continues to increase, it is expected that the volume of uncompressed data produced by hospitals will exceed capacity and drive up costs. The improved compression performance will be accomplished by making use of clinically relevant regions as defined by physicians. This work compared Discrete Cosine Transform (DCT) compression technique and Wavelet Transform (WT) compression techniques for medical images. The result showed compression ratio of 10:1 and 7:1 for DCT and WT respectively. The mean difference of 77.84 with standard deviation of 83.17 and mean difference of 77.77 with standard deviation of 83.23 from the original image were recorded for DCT and WT compression technique.