Fractal S
This invention provides an improved method for evaluating the quality of images using a test S kr -matrix system. The index k refers to the fractal level in an S kr -matrix, having matrices themselves as elements. The index r≦k refers to the Kronecker sub-level to which a typical internal sum structure is present. S kr -matrices can be explained in terms of cognition numbers, basic components, eigenvalues and sine-like eigenvectors. S kr -matrices also form vector spaces in which matrix distances can be properly calculated. The image S kr -quality parameters are derived from an intermediate quasi-S kr -matrix and its best-S kr -approximation in relation to a theoretical reference S kr -matrix. Useful applications are in the field of analogue and digital cameras, scanners, vision sensors, monitors, printers, spectrophotometers, infrared cameras, copying machines, TV-screens, GPS screens, X-rays, Gamma rays, Laser rays, or every other component in the image production and image handling field.
1. A method of evaluating image quality of an image with a processor, the method comprising:
a) generating an Sk,r-image of an object using an optical device;
b) defining an actual Sk,r-matrix for said generated Sk,r-image, said actual Sk,r-matrix comprising a value for each pixel of the generated Sk,r-image;
c) providing a test matrix system comprising a plurality of reference Sk,r-matrices which define a plurality of corresponding reference Sk,r-images, wherein each reference Sk,r-matrix comprises a value for each pixel of the corresponding reference Sk,r-image, and wherein the reference Sk,r-matrices have an internal Sk,r-matrix structure, wherein k and r are different from zero;
d) selecting one of the reference Sk,r-matrices as a best-fit matrix, the best-fit matrix having a best-fit with the actual Sk,r-matrix; and
e) determining image Sk,r-quality parameters of the generated Sk,r-image based on the best-fit matrix,
wherein the method is performed in conjunction with a processor, and wherein the actual Sk,r-matrix and the reference Sk,r-matrices are formed such that for each matrix, every order with respect to r and with respect to the matrix dimensions spans a unique space.
2. The method according to claim 1 , further comprising selecting a region of interest (ROI) on the generated Sk,r-image for evaluating the image quality of said generated Sk,r-image.
3. The method according to claim 1 , wherein the method further comprises:
correcting the image Sk,r-quality parameters of the generated Sk,r-image such that the generated Sk,r-image more closely fits standard image Sk,r-quality parameters; and
visually displaying the generated Sk,r-image after image correction.
4. The method according to claim 1 , wherein the image Sk,r-quality parameters are corrected by correcting operational parameters of the optical device with a software program based on self-tuning algorithms.
5. The method according to claim 1 , wherein said image comprises a sequence of images.
6. The method according to claim 1 , wherein said test matrix system comprises reference Sk,r-matrices each having only one eigenvalue which differs from zero.
7. The method according to claim 1 , wherein the test matrix system comprises reference Sk,r-matrices which are the Kronecker product of two or more Sk,r-matrices having an internal S k,r sum structure.
8. The method according to claim 1 , further comprising determining image Sk,r-quality parameters of the generated Sk,r-image on a two dimensional basis.
9. The method according to claim 1 , further comprising evaluating optical quality of the optical device.
10. The method according to claim 1 , further comprising calibrating the optical device.
11. The method according to claim 1 , wherein the actual Sk,r-matrix and the reference Sk,r-matrices comprise elements which are matrices.
12. The method according to claim 1 , wherein the image Sk,r-quality parameters of the generated Sk,r-image comprise at least one of gamma factor, sharpness, resolution, brightness, contrast, intensity, gamut, symmetry, color coherence, and radial distortion.
13. A non-transitory computer readable medium comprising instructions, which when executed, cause the computer to perform a method of evaluating image quality of an image with a processor, the method comprising:
a) generating an Sk,r-image of an object using an optical device;
b) defining an actual Sk,r-matrix for said generated Sk,r-image, said actual Sk,r-matrix comprising a value for each pixel of the generated Sk,r-image;
c) providing a test matrix system comprising a plurality of reference Sk,r-matrices which define a plurality of corresponding reference Sk,r-images, wherein each reference Sk,r-matrix comprises a value for each pixel of the corresponding reference Sk,r-image, and wherein the reference Sk,r-matrices have an internal Sk,r-matrix structure, wherein k and r are different from zero;
d) selecting one of the reference Sk,r-matrices as a best-fit matrix, the best-fit matrix having a best-fit with the actual Sk,r-matrix;
e) determining image Sk,r-quality parameters of the generated Sk,r-image based on the best-fit matrix; and
f) generating a report of the image Sk,r-quality parameters of the generated Sk,r-image,
wherein the actual Sk,r-matrix and the reference Sk,r-matrices are formed such that for each matrix, every order with respect to r and with respect to the matrix dimensions spans a unique space.
14. A method of evaluating image quality of an image with a processor, the method comprising:
defining an actual Sk,r-matrix for a generated Sk,r-image, said actual Sk,r-matrix comprising a value for each pixel of the generated Sk,r-image;
providing a test matrix system comprising a plurality of reference Sk,r-matrices which define a plurality of corresponding reference Sk,r-images, wherein each reference Sk,r-matrix comprises a value for each pixel of the corresponding reference Sk,r-image, and wherein the reference Sk,r-matrices have an internal Sk,r-matrix structure, wherein k and r are different from zero;
selecting one of the reference Sk,r-matrices as a best-fit matrix, the best-fit matrix having a best-fit with the actual Sk,r-matrix;
determining image Sk,r-quality parameters of the generated Sk,r-image based on the best-fit matrix; and
generating a report of the image Sk,r-quality parameters of the generated Sk,r-image,
wherein the method is performed in conjunction with a processor, and wherein the actual Sk,r-matrix and the reference Sk,r-matrices are formed such that for each matrix, every order with respect to r and with respect to the matrix dimensions spans a unique space.