Image process with spatial periodicity measure
AssigneeSnell Limited
InventorMichael James Knee
Life of this patent
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Abstract
An image manipulation process is controlled by a spatial periodicity measure formed for an image or an image block by measuring the sparseness of the two-dimensional spatial frequency spectrum of the image on a scale of zero to unity in which a two-dimensional spatial frequency spectrum having all equal values has a sparseness of zero and in which a two-dimensional spatial frequency spectrum having only one non-zero value has a sparseness of unity. Sparseness may be measured by allocating values of the spectrum to frequency bins and counting the number of bins that contain non-zero values; comparing values of the spectrum with a threshold and counting the number of values that exceed the threshold; or forming a function of the mean-square value and the mean value of the spectrum values.
Claims20
A non-transitory computer-readable medium including instructions configured to cause a computer system to implement a method comprising the steps of:
- forming a spatial periodicity measure for at least part of an image;
- and
- controlling an image manipulation process in dependence on said spatial periodicity measure;
- wherein the step of forming a spatial periodicity measure comprises:
- measuring the sparseness of the two-dimensional spatial frequency spectrum of the image on a scale of zero to unity in which a two-dimensional spatial frequency spectrum having all equal values has a sparseness of zero and in which a two-dimensional spatial frequency spectrum having only one non-zero value has a sparseness of unity;
- and
- deriving a spatial periodicity measure data that is a function of said sparseness of the two-dimensional spatial frequency spectrum.
A non-transitory computer-readable medium including instructions configured to cause a computer system to implement a motion compensated image manipulation process comprising the steps of:
- forming a spatial periodicity measure for at least part of an image;
- and
- controlling motion compensation of said motion compensated image manipulation process in dependence on said spatial periodicity measure;
- wherein the step of forming a spatial periodicity measure comprises:
- measuring the sparseness of the two-dimensional spatial frequency spectrum of the image utilizing a technique selected from the group of:
- allocating values of the spectrum to frequency bins and counting the number of bins that contain non-zero values;
- comparing values of the spectrum with a threshold and counting the number of values that exceed the threshold;
- comparing values of the spectrum with a representative value for the spectrum and counting the number of values that exceed the representative value;
- and forming a function of the mean-square value of the spectrum values and the mean value of the spectrum values;
- and
- deriving a spatial periodicity measure data that is a function of said sparseness of the two-dimensional spatial frequency spectrum.
A method of controlling a motion compensated image manipulation process in a processor, the method comprising the steps of:
- forming a spatial periodicity measure for at least part of an image;
- and
- controlling motion compensation of said image manipulation process in dependence on said spatial periodicity measure;
- wherein the step of forming a spatial periodicity measure comprises:
- measuring the sparseness of the two-dimensional spatial frequency spectrum of the image utilizing a technique selected from the group of:
- allocating values of the spectrum to frequency bins and counting the number of bins that contain non-zero values;
- comparing values of the spectrum with a threshold and counting the number of values that exceed the threshold;
- comparing values of the spectrum with a representative value for the spectrum and counting the number of values that exceed the representative value;
- and forming a function of the mean-square value of the spectrum values and the mean value of the spectrum values;
- and
- deriving a spatial periodicity measure data that is a function of said sparseness of the two-dimensional spatial frequency spectrum.
Dependencies are inferred from the claim text.