Mutual information-based evaluation of image quality with its preliminary application to assessment of medical imaging systems

摘要

We describe an information-theoretic method for quantifying overall image quality in terms of mutual information (MI). MI is used to express the amount of information that an output image contains about an input object. The more the MI value provides, the better the image quality is. Therefore, the overall quality of an image can be quantitatively evaluated by measuring MI. We demonstrated by way of image simulation that MI increases with increasing contrast and decreases with the increase of noise and blur. We investigated the utility of this method by applying it to evaluate the performance of four imaging plate detectors. We also compared evaluation results in terms of MI against those in terms of the detective quantum efficiency conventionally used for characterizing the efficiency performance of imaging systems. Our results demonstrate that the proposed method is simple to implement and has potential usefulness for evaluation of overall image quality.