  The quality of visual input is very important for both human and machine
perception. Consequently many processing techniques exist that deal with
different distortions. Usually image processing is applied freely and lacks
redundancy regarding safety. We propose a novel image comparison method called
the Combined Distances of Contrast Distributions (CD2) to protect against
errors that arise during processing. Based on the distribution of image
contrasts a new reduced-reference image quality assessment (IQA) method is
introduced. By combining various distance functions excellent performance on
IQA benchmarks is achieved with only a small data and computation overhead.
