Tektronix, Inc.

Bei Li

Bozidar Janko

Wilfried M Osberger

A method for determine blurring in a test video sequence due to video processing includes detecting blocks within each frame of the test video sequence that have valid image edges. An edge point within each valid image edge block is selected and a series of points defining an edge profile in the block along a line normal to the valid image edge at each edge point is defined from an enhanced edge map in which video processing blockiness artifacts have been removed. From the edge profile a blurring value is estimated for each frame or group of frames within the test video sequence. Additionally a reference blurring value may be derived from a reference video sequence corresponding to the test video sequence, which reference blurring value may be generated at a source of the reference video sequence and transmitted with the test video sequence to a receiver or may be generated at the receiver. The reference blurring value is then compared with the blurring value from the test video sequence to produce a relative blurring value for the test video sequence.

Measurement of blurring in video sequences

A method and apparatus for the detection of Gaussian noise in a video signal decomposes an image from the video signal to obtain best qualified blocks having a relatively uniform luminance. From the best qualified blocks an average standard deviation is calculated, and then smoothed by temporal filtering. The filtered average standard deviation is finally calibrated against a scale of corresponding input noise levels to obtain the Gaussian noise in the video signal.

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Beaverton, OR, United States of America

Bei Li