ABSTRACT In digital radiographic systems, a tradeoff exists between image resolution (or blur) and noise characteristics. An imaging system may only be superior in one image quality characteristic while being inferior to another in the other characteristic. In this work, a computer simulation model is presented that is to use mutual-information (MI) metric to examine tradeoff behavior between resolution and noise. MI is used to express the amount of information that an output image contains about an input object. The basic idea is that when the amount of the uncertainty associated with an object before and after imaging is reduced, the difference of the uncertainty is equal to the value of MI. The more the MI value provides, the better the image quality is. The simulation model calculated MI as a function of signal-to-noise ratio and that of resolution for two image contrast levels. Our simulation results demonstrated that MI associated with overall image quality is much more sensitive to noise compared to blur, although tradeoff relationship between noise and blur exists. However, we found that overall image quality is primarily determined by image blur at very low noise levels.
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