Image processing method and apparatus

1. An image processing method, comprising:

receiving an image including frames captured over time in a light environment including an alternating current (AC) light;

extracting AC pixels corresponding to the AC light from pixels in the image;

estimating visual spaces of the AC pixels based on values of the AC pixels in the frames;

estimating intersection lines of the visual spaces;

determining an intersection line that minimizes a cost function, from among the intersection lines;

estimating information of the AC light included in the image based on the determined intersection line; and

processing the image based on the information of the AC light.

2. The image processing method of claim 1 , wherein the estimating of the visual spaces comprises estimating visual spaces indicating illumination components and diffuse components of the AC pixels in the frames.

3. The image processing method of claim 1 , wherein the estimating of the visual spaces comprises estimating dichromatic planes of the AC pixels based on a dichromatic model.

4. The image processing method of claim 1 , wherein the values of the AC pixels comprise red component values, green component values, and blue components of the AC pixels, and

the estimating of the visual spaces comprises estimating the visual spaces based on a linear combination of the red component values, the green component values, and the blue component values of the AC pixels in the frames.

5. The image processing method of claim 1 , wherein the estimating of the visual spaces comprises extracting parameters of the visual spaces that minimize vertical distances between a plane and the values of the AC pixels in the frames.

6. The image processing method of claim 5 , wherein the extracting of the parameters comprises extracting the parameters based on a least squares method.

7. The image processing method of claim 1 , wherein the estimating of the information of the AC light comprises estimating color information of the AC light.

8. The image processing method of claim 1 , wherein the information of the AC light comprises a ratio of red, green, and blue components of the AC light.

9. The image processing method of claim 1 , wherein the processing of the image comprises correcting a color of the image based on color information of the AC light.

10. The image processing method of claim 1 , wherein the extracting of the AC pixels comprises extracting the AC pixels, from among the pixels, exhibiting a signal distortion by noise that is less than a threshold.

11. The image processing method of claim 1 , wherein the extracting of the AC pixels comprises extracting the AC pixels based on variations of values of the pixels in the frames.

12. The image processing method of claim 1 , wherein the extracting of the AC pixels comprises:

modeling values of the pixels in the frames into a sinusoid;

calculating respective differences between the pixel values of the modeled sinusoid and the values of the pixels in the frames; and

extracting, as the AC pixels from the pixels, pixels having a sum of the calculated differences lesser than a threshold.

13. The image processing method of claim 12 , wherein the modeling comprises modeling the values of the pixels in the frames into the sinusoid based on a Gauss-Newton method.

14. The image processing method of claim 1 , wherein the estimating of the information of the AC light comprises:

determining light vector candidates corresponding to the AC light based on the visual spaces;

determining a light vector from among the light vector candidates, based on prior information of the AC light; and

estimating the information of the AC light based on the light vector.

15. The image processing method of claim 14 , wherein the prior information is obtained based on Planckian locus information.

16. The image processing method of claim 1 , wherein the determining of the intersection line comprises:

determining the intersection line based on a maximum a posteriori probability (MAP) estimation.

17. The image processing method of claim 16 , wherein the determining comprises:

calculating probabilities of the intersection lines being perpendicular to the visual spaces; and

determining an intersection line which minimizes a cost function, from among the intersection lines, based on prior information of the AC light and the probabilities.

18. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the image processing method of claim 1 .

19. An image processing apparatus, comprising:

a processor configured to receive an image including frames captured over time in a light environment including an alternating current (AC) light, to extract AC pixels corresponding to the AC light from pixels in the image, to estimate visual spaces of the AC pixels based on values of the AC pixels included in the frames, to estimate intersection lines of the visual spaces, to determine an intersection line that minimises a cost function, from among the intersection lines, and to estimate information of the AC light included in the image based on the determined intersection line, and to process the image based on the information of the AC light.

20. The image processing apparatus of claim 19 , wherein the processor is further configured to estimate visual spaces indicating illumination components and diffuse components of the AC pixels in the frames.

21. The image processing apparatus of claim 19 , wherein the processor is further configured to estimate dichromatic planes of the AC pixels based on a dichromatic model.

22. The image processing apparatus of claim 19 , wherein the values of the AC pixels comprise red component values, green component values, and blue components of the AC pixels, and

the processor is further configured to estimate the visual spaces based on a linear combination of the red component values, the green component values, and the blue component values of the AC pixels in the frames.

23. The image processing apparatus of claim 19 , wherein the processor is further configured to extract parameters of the visual spaces that minimize vertical distances between a plane and the values of the AC pixels in the frames.

24. The image processing apparatus of claim 19 , wherein the processor is further configured to estimate color information of the AC light.

25. The image processing apparatus of claim 19 , wherein the processor is further configured to correct a color of the image based on color information of the AC light.

26. The image processing apparatus of claim 19 , wherein the processor is further configured to extract, as the AC pixels, pixels showing a signal distortion by noise which is less than a threshold, from the pixels.

27. The image processing apparatus of claim 19 , wherein the processor is further configured to extract the AC pixels based on variations of values of the pixels included in the frames.

28. The image processing apparatus of claim 19 , wherein the processor is further configured to model values of the pixels in the frames into a sinusoid, to calculate respective differences between the pixel values of the modeled sinusoid and the values of the pixels in the frames, and to extract, as the AC pixels from the pixels, pixels having sum of the calculated differences lesser than a threshold.

29. The image processing apparatus of claim 28 , wherein the processor is further configured to model the values of the pixels included in the frames into the sinusoid based on a Gauss-Newton method.

30. The image processing apparatus of claim 19 , wherein the processor is further configured to determine light vector candidates corresponding to the AC light based on the visual spaces, to determine a light vector from among the light vector candidates, based on prior information of the AC light, and to estimate the information of the AC light based on the light vector.

31. The image processing apparatus of claim 19 , wherein the processor is further configured to determine the intersection line based on a maximum a posteriori probability (MAP) estimation.

32. The image processing apparatus of claim 31 , wherein the processor is further configured to calculate probabilities of the intersection lines being perpendicular to the visual spaces, and to determine an intersection line which minimizes a cost function, from among the intersection lines, based on prior information of the AC light and the probabilities.