Medical image compression using wavelet transforms and variable block size coding

In recent years, the medical community has seen a growing need for the development of rapid and efficient techniques for the storage and transmission of medical images. Although several well known compression techniques exist, many of them require computationally intensive algorithms. In addition, many image compression techniques introduce unwanted attributes such as the blocking effect or noise. This is a major problem in medical imaging where image degradation may be critical. The aim of our research was to combine two recent techniques, wavelet transforms (WT) and variable block size coding (VBSC), to improve compression ratios as well as visual quality. Multiresolution wavelet transforms are capable of extracting salient features from the image, and thus, allow the decision on the size of block coding. In addition, this hybrid technique reduces noise in the reconstructed images. The image quality is judged by criteria such as entropy, mean square error, signal to noise ratio, and human visual perception. The performance of the hybrid technique is based on the above criteria and compared with the performance of the standard JPEG compression technique. This hybrid compression technique yields improved compression while retaining high visual quality for specific medical images such as cervical radiographs.