Causes and subjective evaluation of blurriness in video frames

A method to automatically assess the seriousness of the blurriness artifact in video frames displayed on a state-of-the-art TV monitor is presented. Different types of the artifact are identified, depending on the stage of the video chain where they are originated, namely, blur produced during acquisition, post-processing and encoding. Every type is observed to produce slightly different effects on the frame and, more importantly, to affect image quality differently, so that distinguishing among types is necessary to perform an appropriate restoration. Two main metrics are therefore introduced for classifying the type of blurriness and, when useful, measuring its strength. Particular care was taken in distinguishing the intentional background blur, which does not cause an actual degradation in the frame quality. The appropriateness of the method in classifying the artifact and predicting the subjective frame quality was verified in the experiments.

► Different types of blurriness in video frames are classified and measured. ► Encoding blurriness, poor resolution and background defocus are the examined types. ► Two metrics are introduced to classify and quantify the artifact. ► Experiments show that measured values comply with evaluations of human observers.