Method of improving a digital image as a function of its dynamic range
First Claim
1. A method of processing a digital image, comprising the steps of:
- providing digital data indexed to represent positions of an image having S spectral bands for simultaneous output on a display, said digital data being indicative of an intensity value Ii(x,y) for each position (x,y) in each i-th spectral band;
defining a classification of said image based on dynamic range of said image in each of said S spectral bands;
adjusting said intensity value for said each position in each i-th spectral band to generate an adjusted intensity value for said each position in each i-th spectral band in accordance with where S is the number of unique spectral bands included in said digital data and, for each n, Wn is a weighting factor and Fn(x,y) is a unique surround function applied to said each position (x,y) and N is the total number of unique surround functions; and
filtering said adjusted intensity value for said each position of said image in each of said S spectral bands using a filter function based on said classification of said image wherein a filtered intensity value Ri(x,y) is defined.
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Abstract
The present invention is a method of processing a digital image that is initially represented by digital data indexed to represent positions on a display. The digital data is indicative of an intensity value Ii(x,y) for each position (x,y) in each i-th spectral band. A classification of the image based on its dynamic range is then defined in each of the image'"'"'s S spectral bands. The intensity value for each position in each i-th spectral band is adjusted to generate an adjusted intensity value for each position in each i-th spectral band in accordance with
where Wn is a weighting factor, “*” is the convolution operator and S is the total number of unique spectral bands. For each n, the function Fn(x,y) is a unique surround function applied to each position (x,y) and N is the total number of unique surround functions. Each unique surround function is scaled to improve some aspect of the digital image, e.g., dynamic range compression, color constancy, and lightness rendition. The adjusted intensity value for each position in each i-th spectral band of the image is then filtered with a filter function that is based on the dynamic range classification of the image.
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Citations
26 Claims
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1. A method of processing a digital image, comprising the steps of:
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providing digital data indexed to represent positions of an image having S spectral bands for simultaneous output on a display, said digital data being indicative of an intensity value Ii(x,y) for each position (x,y) in each i-th spectral band;
defining a classification of said image based on dynamic range of said image in each of said S spectral bands;
adjusting said intensity value for said each position in each i-th spectral band to generate an adjusted intensity value for said each position in each i-th spectral band in accordance with where S is the number of unique spectral bands included in said digital data and, for each n, Wn is a weighting factor and Fn(x,y) is a unique surround function applied to said each position (x,y) and N is the total number of unique surround functions; and
filtering said adjusted intensity value for said each position of said image in each of said S spectral bands using a filter function based on said classification of said image wherein a filtered intensity value Ri(x,y) is defined. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of processing a digital image, comprising the steps of:
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providing digital data indexed to represent the positions of a plurality of pixels of a J-row by K-column display, said digital data being indicative of an intensity value I(x,y) for each of said plurality of pixels where x is an index of a position in the J-th row of said display and y is an index of a position in the K-th column of said display wherein a J×
K image is defined;
convolving said digital data associated with each of said plurality of pixels with a function to form a discrete convolution value for each of said plurality of pixels, said function satisfying the relationship where r={square root}{square root over (x2+y2)} k is a normalization constant and c is a constant;
converting, for each of said plurality of pixels, said discrete convolution value into the logarithm domain;
converting, for each of said plurality of pixels, said intensity value into the logarithm domain;
subtracting, for each of said plurality of pixels, said discrete convolution value so-converted into the logarithm domain from said intensity value so-converted into the logarithm domain, wherein an adjusted intensity value is generated for each of said plurality of pixels; and
filtering said adjusted intensity value for each of said plurality of pixels with a filter function that is based on dynamic range of said J×
K image wherein a filtered intensity value R(x,y) is defined. - View Dependent Claims (12, 13)
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14. A method of processing a digital image, comprising the steps of:
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providing digital data indexed to represent the positions of a plurality of pixels of an J-row by K-column display, said digital data being indicative of an intensity value Ii(x,y) for each i-th spectral band of S spectral bands for each of said plurality of pixels where x is an index of a position in the J-th row of said display and y is an index of a position in the K-th column of said display wherein a (J×
K)i image is defined for each of said S spectral bands and a J×
K image is defined across all of said S spectral bands;
defining a classification of said J×
K image based on dynamic range of each said (J×
K)i;
convolving said digital data associated with each of said plurality of pixels in each i-th spectral band with a function for n=2 to N to form N convolution values for each of said plurality of pixels in each said i-th spectral band, said function satisfying the relationship where r={square root}{square root over (x2+y2)} and, for each n, kn is a normalization constant and cn is a unique constant;
converting, for each of said plurality of pixels in each said i-th spectral band, each of said N convolution values into the logarithm domain;
converting, for each of said plurality of pixels in each said i-th spectral band, said intensity value into the logarithm domain;
subtracting, for each of said plurality of pixels in each said i-th spectral band, each of said N convolution values so-converted into the logarithm domain from said intensity value so-converted into the logarithm domain, wherein an adjusted intensity value is generated for each of said plurality of pixels in each said i-th spectral band based on each of said N convolution values;
forming a weighted sum for each of said plurality of pixels in each said i-th spectral band using said adjusted intensity values; and
filtering said weighted sum for each of said plurality of pixels in each said i-th spectral band with a filter function that is based on said classification of said J×
K image wherein a filtered intensity value Ri(x,y) is defined. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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21. A method of processing a digital image, comprising the steps of:
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providing digital data indexed to represent positions of an image having S spectral bands for simultaneous output on a display, said digital data being indicative of an intensity value I1(x,y) for each position (x,y) in each i-th spectral band;
defining a classification of said image based on dynamic range of said image in each of said S spectral bands;
adjusting said intensity value for said each position in each i-th spectral band to generate an adjusted intensity value for said each position in each i-th spectral band in accordance with where S is a whole number greater than or equal to 2 and defines the total number of spectral bands included in said digital data and, for each n, Wn is a weighting factor and Fn(x,y) is a unique surround function of the form satisfying the relationship where r={square root}{square root over (x2+y2)} and, for each n, kn is a normalization constant and cn is a unique constant where N is the total number of unique surround functions;
filtering said adjusted intensity value for said each position in each i-th spectral band with a function based on said classification of said image wherein a filtered intensity value Ri(x,y) is defined; and
multiplying said filtered intensity value Ri(x,y) by to define a color-restored intensity value R′
i(x,y), where B is a constant. - View Dependent Claims (22, 23, 24, 25, 26)
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Specification