Automatic quality control of digital image content reconstruction schemes

In this study we address the problem of an image quality trade-off that can be observed when dealing with content reconstruction schemes based on self-embedding. We derive two models for the estimation of optimal system parameters and the optimization of the overall image quality. This goal is achieved by balancing the distortions of a different nature that affect the resulting images. The performance of the derived models is verified with an accurate reference model and compared to traditional parameter selection strategies. The models are based on basic image features only and allow for rapid prediction of the best values for system parameters in a fully automatic manner.