Method of chromatic classification of pixels and method of adaptive enhancement of a color image

1. A method, comprising:

chromatic classifying pixels of a digital image by,

transforming a chromatic domain of definition of pixels from a three-dimensional space into a respective two-dimensional normalized space;

defining a reference model of classification by analyzing a plurality of images of distinct types of subjects, generating distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects; and

evaluating for each image pixel to be classified a membership class and a membership level within the membership class based on the reference model,

wherein said reference model is defined by a parametric membership function continuous on said normalized two-dimensional space for each of said chromatic classes, parameters of which are determined by processing the collection of two-dimensional samples of each of said chromatic classes, said chromatic classifying, transforming, defining and evaluating are performed by one or more configured processing devices, and wherein defining the reference model comprises calculating a mean position of clusters of samples on the normalized two-dimensional space, a variance in respect to a principal direction and to a direction orthogonal to said principal direction and a slope angle of said principal direction using a principal component analysis technique, thus obtaining an elliptical Gaussian model for each of said chromatic classes on said normalized two-dimensional space.

2. The method of claim 1 wherein said three-dimensional space is an RGB space and the respective normalized two-dimensional space is an rg space.

3. The method of claim 1 wherein for each membership class a relative membership value is obtained for a current pixel being processed, a maximum membership value being established in function of the respective membership class, and the membership level being determined in function of a maximum quantized value with a number of bits.

4. The method of claim 1 , further comprising storing in array values of said reference model in correspondence of pairs of values in the normalized two-dimensional space, and of determining the membership level of each pixel by reading from the array a value corresponding to the pair that represents said pixel in the normalized two-dimensional space.

5. The method of claim 1 , comprising steps of:

verifying whether levels of the membership functions in correspondence of a neutral axis are smaller than a threshold; and

reducing proportionally the variances of membership functions for which the verification of the previous step is not satisfied, such that a respective value of the membership level of said neutral axis is smaller than said threshold.

6. The method of claim 5 wherein said threshold is 2%.

7. A method, comprising:

chromatic classifying pixels of a digital image by,

transforming a chromatic domain of definition of pixels from a three-dimensional space into a respective two-dimensional normalized space;

defining a reference model of classification by analyzing a plurality of images of distinct types of subjects, generating distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects; and

evaluating for each image pixel to be classified a membership class and a membership level within the membership class based on the reference model; and

storing in array values of said reference model in correspondence of pairs of values in the normalized two-dimensional space, wherein determining the membership level of each pixel includes reading from the array a value corresponding to the pair that represents said pixel in the normalized two-dimensional space, wherein:

said reference model is defined by a parametric membership function continuous on said normalized two-dimensional space for each of said chromatic classes, parameters of which are determined by processing the collection of two-dimensional samples of each of said chromatic classes, said chromatic classifying, transforming, defining and evaluating are performed by one or more configured processing devices, and

the stored values in said two-dimensional array are obtained through steps of:

on clusters of samples of said images of distinct types of subjects, calculating a mean position, a variance in respect to a principal direction, a variance in respect to a direction orthogonal to the principal direction and a slope angle of the principal direction;

generating values according to an elliptical Gaussian model in the normalized two-dimensional space; and

undersampling and quantizing the values obtained at a previous point and storing them in the two-dimensional array.

8. A method, comprising:

chromatic classifying pixels of a digital image by,

transforming a chromatic domain of definition of pixels from a three-dimensional space into a respective two-dimensional normalized space;

defining a reference model of classification by analyzing a plurality of images of distinct types of subjects, generating distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects; and

evaluating for each image pixel to be classified a membership class and a membership level within the membership class based on the reference model;

generating a membership image of pixels of the digital image with the chromatic classes of the reference model;

defining a table of chromaticity target values for each chromatic class;

converting definition values of each pixel of an image to be processed from the chromatic definition domain to the respective normalized two-dimensional space;

calculating for each cluster of pixels belonging to a chromatic class a pair of statistic parameters;

calculating for each cluster a distance from a respective chromaticity target value;

determining for each pixel of the image belonging to a respective chromatic class, respective values in the chromatic definition domain corrected in function of coordinates of original values in the respective normalized two-dimensional space and of the distance of the relative cluster from a relative target color; and

carrying out a modulated correction of a color of the pixel using a weighted linear combination of the values of the pixel and of said triplet of target values, wherein said reference model is defined by a parametric membership function continuous on said normalized two-dimensional space for each of said chromatic classes, parameters of which are determined by processing the collection of two-dimensional samples of each of said chromatic classes, said chromatic classifying, transforming, defining and evaluating are performed by one or more configured processing devices.

9. The method of claim 8 wherein said weighted linear combination is carried out using weights determined in function of the membership levels such that an intensity of pixels of the enhanced image is equal to an intensity of the corresponding pixel of the image to be enhanced.

10. A method of processing pixels in a digital image, the method comprising:

generating, using one or more configured processing devices, a membership image of pixels of the digital image based on chromatic classes of a reference model and membership levels of pixels of the digital image in the chromatic classes of the reference model;

defining, using the one or more configured processing devices, a table of chromaticity target values for each chromatic class;

calculating, using the one or more configured processing devices, for each cluster of pixels belonging to a chromatic class a pair of statistic parameters;

calculating, using the one or more configured processing devices, for each cluster a distance from a respective chromaticity target value;

determining, using the one or more configured processing devices, for each pixel of the image belonging to a respective chromatic class, respective values in the chromatic definition domain corrected in function of coordinates of original values in the respective normalized two-dimensional space and of the distance of the relative cluster from a relative target color; and

carrying out, using the one or more configured processing devices, a modulated correction of a color of the pixel using a weighted linear combination of the values of the pixel and of said triplet of target values.

11. The method of claim 10 wherein said weighted linear combination is carried out using weights determined in function of the membership levels such that an intensity of pixels of the enhanced image is equal to an intensity of the corresponding pixel of the image to be enhanced.