A set of features for measuring blurriness in video frames

A new method to assess the presence and the strength of the blurring artefact in video frames is presented. The estimation is performed first through a global and simple measure over the whole picture, then through a finer, block-level analysis of the sharpness of the objects borders. The subjective relevance of blurriness in different parts of the scene is estimated, using an existing visual attention method that estimates the perceptive relevance of each pixel. Then the scene activity, or clutter, is measured by counting the number of distinct picture regions. In an active scene, indeed, a blurred object is deemed to be less apparent. Finally a method is devised to find human faces, image parts a human viewer will most of the time look at. The parameters obtained through a combination of objective measurements and subjective relevance respond coherently to changes in image quality due to different video encodings, as experimental results show.