Image based learning correction for mitigating thermal ghosting in a digital printer

Abstract

An image based correction system compensates for the image quality artifacts induced by thermal ghosting on evolving imaging member surfaces. With thermal ghosting directly tied to previous image content, a feed forward system determines thermal ghosting artifacts based on images previously rendered and generates an open loop gray-level correction to a current image that mitigates undesirable ghosting. For example, the correction system compensates for the thermal ghosting by making the current image 'lighter' in areas that will be imaged onto warmer blanket regions, thereby cancelling out TRC differences between different temperature regions. A temperature sensor is used to measure the temperature of the imaging blanket due to the stresses induced by the image. This data is used to learn the parameters of the temperature model periodically during operation, and used in subsequent corrections to mitigate thermal ghosting in spite of changes in blanket properties over use and time.