Perceptual image quality assessment metric that handles arbitrary motion blur

Abstract

A fair knowledge of the human hand tremor responsible for camera-shake noise as well as a way to measure the impact of motion-blur on human-perceived image quality are mandatory to quantify the gain of image stabilization systems. In order to define specifications for the stabilization chain we have derived a perceptual image quality metric for camera-shake induced motion blur. This quality metric was validated with visual tests. Comparison to the ground-truth shows a good fitting in the simple case of straight-line motion blur as well as a fair fitting in the more complex case of arbitrary motion blur. To our best knowledge this is the first metric that can predict image quality degradation in the case of arbitrary blur. The quality model on which this metric is based gives some valuable insights on the way motion blur impacts perceived quality and can help the design of optimal image stabilization systems.