Image Quality Optimization
One of the most important aspects of an image processing pipeline is the image itself and its quality. Quality can be defined in many different ways and includes typically metrics that take into account contrast, resolution, frame rate, signal to noise ratio, etc... Our ability to control the image formation itself allows us to reconsider some steps involved in the imaging sequence and the image reconstruction processing. Research on image quality optimization is performed in the group along the three following axes.