Method and system for increasing robustness of visual quality metrics using spatial shifting
First Claim
1. A method of computing a measure of quality for a distorted image Y, the measure characterizing a similarity between the image Y and an undistorted reference image X having the same number of rows and columns of pixels as the image Y, the method comprising:
- employing at least one processor for;
(a) transforming the distorted image Y and the undistorted reference image X by a transformation process to generate a transform of the distorted image Y and a transform of the undistorted reference image X respectively, the transformation process having a blindness property of not containing all information regarding an image to be transformed in a transform of the image, thus resulting in certain pixel patterns of the image leading to zero transform coefficients not to be recognized during the transformation process;
(b) spatially shifting pixels in the reference image X and the distorted image Y by a spatial shift, having the same predefined amount of pixels, to generate a spatially shifted version X2 of the reference image X and a spatially shifted version Y2 of the image Y respectively, the spatial shift being chosen so that the certain pixel patterns in images X and Y leading to zero transform coefficients upon applying the transformation process to the images X and Y would lead to non zero values for the transform coefficients upon applying the transformation process to the images X2 and Y2, thereby making the certain patterns detectable by using the transformation process applied to the spatially shifted versions X2 and Y2;
(c) transforming the spatially shifted version Y2 and the spatially shifted version X2 by the transformation process to generate a transform of the spatially shifted version Y2 and a transform of the spatially shifted version X2 respectively; and
(d) determining the measure of quality for the distorted image Y as a function of the transform of the distorted image Y, the transform of the undistorted reference image X, the transform of the spatially shifted version Y2, and the transform of the spatially shifted version X2.
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Abstract
A visual quality assessment method and system are based on deriving a quality metric by comparing sub-band approximations of a distorted image and an undistorted version of the same image, providing a good compromise between computational complexity and accuracy. The sub-band approximations are derived from Discrete Wavelet (Haar) transforms of small image blocks of each image. Due to inherent symmetries, the wavelet transform is “blind” to certain types of distortions. But the accuracy of the method is enhanced, and the blindness of the transform is overcome, by computing quality metrics for the distorted image as well as computing quality metrics for a shifted version of the distorted image and combining the results.
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Citations
34 Claims
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1. A method of computing a measure of quality for a distorted image Y, the measure characterizing a similarity between the image Y and an undistorted reference image X having the same number of rows and columns of pixels as the image Y, the method comprising:
- employing at least one processor for;
(a) transforming the distorted image Y and the undistorted reference image X by a transformation process to generate a transform of the distorted image Y and a transform of the undistorted reference image X respectively, the transformation process having a blindness property of not containing all information regarding an image to be transformed in a transform of the image, thus resulting in certain pixel patterns of the image leading to zero transform coefficients not to be recognized during the transformation process; (b) spatially shifting pixels in the reference image X and the distorted image Y by a spatial shift, having the same predefined amount of pixels, to generate a spatially shifted version X2 of the reference image X and a spatially shifted version Y2 of the image Y respectively, the spatial shift being chosen so that the certain pixel patterns in images X and Y leading to zero transform coefficients upon applying the transformation process to the images X and Y would lead to non zero values for the transform coefficients upon applying the transformation process to the images X2 and Y2, thereby making the certain patterns detectable by using the transformation process applied to the spatially shifted versions X2 and Y2; (c) transforming the spatially shifted version Y2 and the spatially shifted version X2 by the transformation process to generate a transform of the spatially shifted version Y2 and a transform of the spatially shifted version X2 respectively; and (d) determining the measure of quality for the distorted image Y as a function of the transform of the distorted image Y, the transform of the undistorted reference image X, the transform of the spatially shifted version Y2, and the transform of the spatially shifted version X2. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
- employing at least one processor for;
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18. A system for computing a measure of quality for a distorted image Y, the measure characterizing a similarity between the image Y and an undistorted reference image X having the same number of rows and columns of pixels as the image Y, the system comprising:
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a processor; a non-transitory computer readable storage medium having computer readable instructions stored thereon for execution by the processor, causing the processor to; (a) transform the distorted image Y and the undistorted reference image X by a transformation process to generate a transform of the distorted image Y and a transform of the undistorted reference image X respectively, the transformation process having a blindness property of not containing all information regarding an image to be transformed in a transform of the image, thus resulting in certain patterns of the image leading to zero transform coefficients not to be recognized during the transformation process; (b) spatially shift pixels in the reference image X and the distorted image Y by a spatial shift, having the same predefined amount of pixels, to generate a spatially shifted version X2 of the reference image X and a spatially shifted version Y2 of the image Y respectively, the spatial shift being chosen so that the certain pixel patterns in images X and Y leading to zero transform coefficients upon applying the transformation process to the images X and Y would lead to non zero values for the transform coefficients upon applying the transformation process to the images X2 and Y2, thereby making, the certain patterns detectable by using the transformation process applied to the spatially shifted versions X2 and Y2; (c) transform the spatially shifted version Y2 and the spatially shifted version X2 by the transformation process to generate a transform of the spatially shifted version Y2 and a transform of the spatially shifted version X2 respectively; and (d) determine the measure of quality for the distorted image Y as a function of the transform of the distorted image Y, the transform of the undistorted reference image X, the transform of the spatially shifted version Y2, and the transform of the spatially shifted version X2. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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Specification