Apparatus and method for combining random set of video features in a non-linear scheme to best describe perceptual quality of video sequences using heuristic search methodology
First Claim
1. A method for providing a composite objective image quality metric of a set of a plurality of random video features, said method comprising the steps of:
- (a) receiving a video sequence for image quality evaluation;
(b) providing an objective metric image quality controller comprising a random set of metrics ranging from M1 to Mn without cross correlation information for;
(c) applying said each one metric of said set of metrics individually to said video sequence so that said each one metric of said random set of metrics provides an individual objective scoring value of said video sequence ranging from x1 to xn;
(d) determining a plurality of sets of weights (w1 to wn) which correlate to predetermined subjective evaluations of image quality for a predetermined plurality of video sequences (n), each one set of weights of said plurality of sets of weights being assigned a range having an incremental value equal to said range divided by a number of combinations for said each one set of weights;
(e) weighting by said each one set of weights each individual objective scoring value x1 to xn provided by said each one metric of said random set of metrics in step (c);
(f) adding the weighted individual objective scoring values of said random set of metrics into a single objective evaluation F, wherein each weighted individual scoring value from step (e) is multiplied by each individual objective scoring value x1 to xn from step (c);
(g) calculating a correlation factor R to provide a correlation value for the objective evaluation F and the plurality of video sequences (n);
(h) repeating steps (e), (f) and (g) for each set of weights provided in step (d) to determine a plurality of correlation factors R;
(i) ranking said plurality of correlation factors R, wherein a particular correlation factor of said plurality of correlation factors having a particular correlation value closest to 1 represents a best ranking of the respective combined metrics in step (e) for each set of weights; and
(j) providing image quality information to at least one of a system optimizer and the video processing module as to the best ranking of the respective combined metrics obtained in step (i) to provide a best perceptual image quality.
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Abstract
A method for combining a random set of video features non-linearly to evaluate perceptual quality of video sequences includes (a) receiving a video sequence for image quality evaluation; (b) providing an objective metric image quality controller comprising a random set of metrics ranging from M1 to Mn without dependency information for each one metric; (c) applying each one metric individually to the video sequence to provide an individual objective scoring value of the video sequence ranging from x1 to xn; (d) determining a plurality of sets of weights (w1 to wn) which correlate to predetermined subjective evaluations of image quality for a predetermined plurality of video sequences (n), each one set of weights being assigned a range having an incremental value equal to the range divided by a number of combinations for each one set of weights; (e) weighting each individual objective scoring value x1 to xn provided by each one metric of the random set of metrics in step (c); (f) combining metrics of the weighted individual objective scoring value of the random set of metrics into a single objective evaluation F, wherein each weighted individual scoring value from step (e) is multiplied by each individual objective scoring value x1 to xn from step (c); (g) calculating a correlation factor R to provide a correlation value for the objective evaluation F and the plurality of video sequences (n). Steps (e), (f) and (g) are repeated to provide a plurality of correlation factors which are ranked. A heuristic search uses a genetic algorithm to find the best set of weights to provide objective scores closest to predetermined subjective evaluations. A system provides the hardware and modules that perform the non-linear combination of metrics to provide enhanced perceptual image information.
20 Citations
34 Claims
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1. A method for providing a composite objective image quality metric of a set of a plurality of random video features, said method comprising the steps of:
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(a) receiving a video sequence for image quality evaluation;
(b) providing an objective metric image quality controller comprising a random set of metrics ranging from M1 to Mn without cross correlation information for;
(c) applying said each one metric of said set of metrics individually to said video sequence so that said each one metric of said random set of metrics provides an individual objective scoring value of said video sequence ranging from x1 to xn;
(d) determining a plurality of sets of weights (w1 to wn) which correlate to predetermined subjective evaluations of image quality for a predetermined plurality of video sequences (n), each one set of weights of said plurality of sets of weights being assigned a range having an incremental value equal to said range divided by a number of combinations for said each one set of weights;
(e) weighting by said each one set of weights each individual objective scoring value x1 to xn provided by said each one metric of said random set of metrics in step (c);
(f) adding the weighted individual objective scoring values of said random set of metrics into a single objective evaluation F, wherein each weighted individual scoring value from step (e) is multiplied by each individual objective scoring value x1 to xn from step (c);
(g) calculating a correlation factor R to provide a correlation value for the objective evaluation F and the plurality of video sequences (n);
(h) repeating steps (e), (f) and (g) for each set of weights provided in step (d) to determine a plurality of correlation factors R;
(i) ranking said plurality of correlation factors R, wherein a particular correlation factor of said plurality of correlation factors having a particular correlation value closest to 1 represents a best ranking of the respective combined metrics in step (e) for each set of weights; and
(j) providing image quality information to at least one of a system optimizer and the video processing module as to the best ranking of the respective combined metrics obtained in step (i) to provide a best perceptual image quality. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34)
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29. A system for providing a composite image of a random set of video features may comprise:
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means for receiving a video sequence;
an objective metric image quality controller comprising a plurality of objective metrics without prior dependency information thereof and means for selecting a metric from said plurality of objective metrics for evaluating image quality of the video sequence, and means for applying each of said plurality of objective metrics by said objective metric image quality controller to said video sequence and individually scoring said video sequence from x1 to xn;
means for determining a plurality of sets of weights (w1 to wn) by said objective metric image quality controller, said plurality of sets of weights correlate to predetermined subjective evaluations of image quality for a predetermined plurality of video sequences (n), each one set of weights being assigned a range having an incremental value equal to a value of said range divided by a number of combinations for said each one set of weights, which includes means for weighting by said each one set of weights each individual objective scoring value x1 to xn provided by said each one metric of said random set of metrics;
means for combining metrics of the weighted individual objective scoring values of said random set of metrics into a single objective evaluation F, wherein each weighted individual scoring value is multiplied by each individual objective scoring value x1 to xn;
means for calculating a plurality of correlation factors R to provide a correlation value for the objective evaluation F and the plurality of video sequences (n), which includes means for ranking said plurality of correlation factors R, wherein a particular correlation factor of said plurality of correlation factors having a particular correlation value closest to 1 represents a best ranked respective combined metrics for each set of weights;
wherein the best ranked respective combined metrics determined by said objective metric image quality controller is used to provide a best objective perceptual quality of said video sequence.
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Specification