British Telecommunications Public Limited Company

British Telecommunications Corporation

Alexandre J Bourret

Michael Peter Hollier

Andrew Gordon Davis

David S Hands

Damien Bayart

A method and system for automated video quality assessment which reduces the adverse effects of sub-field/frame misalignments between the reference and test sequences. More particularly, the invention provides for misalignments down to a sub-field/frame level to be handled by individually matching sub-field/frame elements of a test video field/frame with sub-field/frame elements from a reference video field/frame. The use of a matching element size that is significantly smaller than the video field/frame size enables transient sub-field/frame misalignments to be effectively tracked.

Method and system for video quality assessment

A system and method for evaluating a video signal comprising a plurality of video frames. In the plurality video frames, the number of pixels changed from one frame to the next are analysed and each frame is identified as being a repeat if a set proportion of the pixels present in the current frame match those present in the previous frame. The resultant pattern of repeat frames in the video signal is recorded. The resultant pattern is then scanned to determine whether or not a given repeat frame is part of a temporally repetitive pattern and those repeat frames not determined to be part of the temporally repetitive pattern are identified. As result of the above, video quality assessment is able to treat these two types of temporal artefact separately so as to distinguish between the almost invisible regular frame loss and the visually disturbing irregular frame loss.

Edge detector techniques, known per se in the art, are applied to the field of automated video quality assessment. Any known edge detection algorithm is used as the basis of an edge detection stage for performing edge analysis of test video fields/frames in order to generate an edge parameter value that can then be used to contribute to an overall video quality value. The use of an edge detector stage contributes valuable information concerning image attributes which are perceptually significant to a human viewer to the quality assessment, thus rendering the result provided by the automated assessment more similar to that which would be performed by a human viewer undertaking a subjective assessment.

Edge analysis in video quality assessment

Two video signals, typically an original signal and a degraded version of the same signal, are analyzed firstly to identify perceptually relevant boundaries of elements forming video images depicted therein. These boundaries are then compared to determine the extent to which the properties of the boundaries defined in one image are preserved in the other, to generate an output indicative of the perceptual difference between the first and second signals. The boundaries may be defined by edges, color, luminance or texture contrasts, disparities between frames in a moving or stereoscopic image, or other means. The presence, absence, difference in clarity or difference in means of definition of the boundaries is indicative of the perceptual importance of the differences between the signals, and therefore of the extent to which any degradation of the signal will be perceived by the human viewer of the resulting degraded image. The results may also be weighted according to the perceptual importance of the image depicted&#x2014;for example the features which identify a human face, and in particular those responsible for visual speech cues.

Analysis of video signal quality

A non-intrusive test method for video sequences correlates a number of quality indicators derived from a sequence with a matrix of constants to predict a quality score for the sequence.

Test method

A method of aligning a first image with a second image, the method includes approximately locating the second image; scaling the first image to the approximate size of the second image; positioning the scaled first image over the approximate location of the second image; generating a measure of fit between the first image and the second image; re-positioning the second image and repeating the above steps to obtain an increased measure of fit value. A method of synchronizing a first sequence of images with a second sequence of images includes creating a first index pointer identifying an image in the first sequence of images; creating a second index pointer identifying an image in the second sequence of images; comparing the image identified by the first index pointer with the image identified by the second index pointer; incrementing the first index pointer to identify the subsequent image in the first sequence of images; and repeating the above steps until the image identified by the first index pointer matches the image identified by the second index pointer.

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Ipswich, United Kingdom

Alexandre J Bourret