A comparative study on state of the art picture coding evaluation for medical image compression

The aim of this paper is to examine and evaluate a suitable image quality metrics as applied to medical image compression based on wavelet transform and figure out why a voluminous range of quality metrics are used ranging from simple objective mathematical assessment to complex subjective analysis. Wavelet based image compression is a cutting edge technology in the field of image processing. One of the main problems and challenges in the image compression schemes is the lack of a well defined and accepted metric for the prediction of image quality of the compressed images. The most commonly, regularly and frequently used image quality metrics for image compression system are remain simple and mathematically tractable such as peak signal to noise ratio (PSNR) or mean squared error (MSE). These simple objective based metrics do not accurately predict the visual quality of medical images which contain a large luminance variations such as edges and textured regions of complex systems of the human body. This study not only highlights how image quality metrics can be used to guide an image compression scheme in general but it also outlines the pros and cons of a number of quality metrics in particular and their limitations to medical images.