Method for differentiating dynamic range of image

1. An apparatus, comprising:

a memory configured to store data associated with an image; and

a controller configured to identify pixel distributions for different density elements of the image, the controller further configured to use the identified pixel distributions to differentiate the different density elements.

2. The apparatus according to claim 1 wherein the controller is further configured to use the pixel distributions to exclude interference in the density elements induced by image obstacles.

3. The apparatus according to claim 1 wherein the controller is further configured to determine which density elements are distinguishable or undistinguishable according to an amount of overlap in the pixel distributions between the different density elements.

4. The apparatus according to claim 1 wherein the controller is further configured to:

identify which pixel level values are common for the different density elements; and

identify minimum pixel numbers for the identified pixel level values.

5. The apparatus according to claim 4 wherein the controller is further configured to:

determine a total minimum pixel number for the identified minimum pixel numbers; and

identify the density elements as distinguishable or undistinguishable by comparing the total minimum pixel number with a predetermined value.

6. The apparatus according to claim 4 wherein the controller is further configured to:

determine a total minimum pixel number for the identified minimum pixel numbers;

determine an overall total pixel number for the density elements;

determine a ratio between the total minimum pixel number and the overall total pixel number; and

identify the density elements as distinguishable or undistinguishable according to the determined ratio.

7. A method, comprising:

storing image elements in a memory and analyzing the image elements using logic circuitry;

identifying pixel-level distributions of the image elements;

identifying an overlap area for the pixel-level distributions; and

identifying the image elements as distinguishable or undistinguishable according to the identified overlap area.

8. The method according to claim 7 further comprising:

identifying pixels for adjacent image elements having common level values;

identifying minimum pixel numbers for the common level values;

summing the minimum pixel numbers for the common level values; and

identifying the image elements as distinguishable or undistinguishable according to the summed minimum pixel numbers.

9. The method according to claim 8 further comprising:

comparing the summed minimum pixel numbers with a predetermined value; and

identifying the image elements as distinguishable or undistinguishable according to the comparison.

10. The method according to claim 8 further comprising:

identifying a total number of pixels for the image elements;

identifying a ratio between the summed minimum pixel numbers and the identified total number of pixels; and

determining the image elements as distinguishable or undistinguishable according to the identified ratio.

11. The method according to claim 7 further comprising excluding the image elements induced by image obstacles.

12. A scanner, comprising:

a sensor configured to generate data associated with pixels; and

logic circuitry configured to detect pixel-level distributions for different density units and identify the pixels in the different density units having overlapping pixel-levels, the logic circuitry further configured to identify which of the different density units are distinguishable or undistinguishable according to the distribution of overlapping pixel-levels.

13. The scanner according to claim 12 wherein the logic circuitry is further configured to:

identify minimum pixel numbers for the overlapping pixel-levels;

sum the identified minimum pixel numbers for the overlapping pixel-levels; and

determine which of the different density units are distinguishable or undistinguishable according to the summed minimum pixel numbers.

14. The scanner according to claim 13 wherein the logic circuitry is further configured to:

compare the summed minimum pixel numbers with a predetermined value; and

identify which of the different density units are distinguishable or undistinguishable according to the comparison.

15. The scanner according to claim 12 wherein the logic circuitry is further configured to:

identify a total number of pixels for the density units;

identify a ratio between the summed minimum pixel numbers and the identified total number of pixels; and

determine which of the different density units are distinguishable or undistinguishable according to the identified ratio.

16. The scanner according to claim 12 wherein the logic circuitry is further configured to exclude the density units induced by image obstacles.

17. The scanner according to claim 12 wherein the logic circuitry is further configured to differentiate a dynamic range of the density units according to the identified overlapping pixel-levels.

18. The scanner according to claim 12 wherein the logic circuitry is further configured to:

compare pixel numbers with a same level value of density units D n−1 and D n ;

count a minimum pixel number of each level value of density units D n−1 and D n ;

sum the minimum pixel number of each level value of density units D n−1 and D n ; and

compare a ratio of total minimum pixel number and total pixel number R with a specification value R s .

19. The scanner according to claim 12 wherein the logic circuitry is further configured to:

provide pixel-level distributions of density units D n−1 and D n ;

count an overlap area of the pixel-level distributions of the density units D n−1 and D n ; and

compare the overlap area with a specification value.

20. A computer readable medium having instructions stored thereon that, when executed by a computer platform, result in:

receiving data associated with an image; and

identifying image distributions for different density elements of the image and using the identified image distributions to differentiate the different density elements.

21. The computer readable medium according to claim 20 further comprising using the image distributions to exclude interference in the density elements induced by image obstacles.

22. The computer readable medium according to claim 20 further comprising determining which density elements are distinguishable or undistinguishable according to an amount of overlap in the image distributions between the different density elements.

23. The computer readable medium according to claim 20 further comprising:

identifying what image level values are common for the different density elements; and

identifying minimum numbers for the identified image level values.

24. The computer readable medium according to claim 23 further comprising:

determining a total minimum number for the identified minimum numbers; and

identifying the density elements as distinguishable or undistinguishable by comparing the total minimum number with a predetermined value.

25. The computer readable medium according to claim 23 further comprising:

determining a total minimum number for the identified minimum numbers;

determining an overall total number for the density elements;

determining a ratio between the total minimum number and the overall total number; and

identifying the density elements as distinguishable or undistinguishable according to the determined ratio.

26. An apparatus, comprising:

means for obtaining data associated with pixels; and

means for identifying pixel-level distributions for different units, identifying the pixels in the different density units having overlapping pixel-levels, and identifying which of the different density units are distinguishable or undistinguishable according to the distribution of overlapping pixel-levels.

27. The apparatus according to claim 26 wherein the means for identifying pixel-level distributions is further configured to:

identify the minimum pixel numbers for the overlapping pixel-levels;

sum the identified minimum pixel numbers for the overlapping pixel-levels; and

determine which of the different density units are distinguishable or undistinguishable according to the summed minimum pixel numbers.

28. The apparatus according to claim 27 wherein the means for identifying pixel-level distributions is further configured to:

compare the summed minimum pixel numbers with a predetermined value; and

identify which of the different density units are distinguishable or undistinguishable according to the comparison.

29. The apparatus according to claim 27 wherein the means for identifying pixel-level distributions is further configured to:

identify a total number of pixels for the density units;

identify a ratio between the summed minimum pixel numbers and the identified total number of pixels; and

determine which of the different density units are distinguishable or undistinguishable according to the identified ratio.

30. The apparatus according to claim 26 wherein the means for identifying pixel-level distributions is further configured to exclude the density units induced by image obstacles.

31. The apparatus according to claim 26 wherein the means for identifying pixel-level distributions is further configured to differentiate a dynamic range of the density units according to the identified overlapping pixel-levels.

32. The apparatus according to claim 26 wherein the means for identifying pixel-level distributions is further configured to:

compare pixel numbers with a same level value of density units D n−1 and D n ;

count a minimum pixel number of each level value of density units D n−1 and D n ;

sum the minimum pixel number of each level value of density units D n−1 and D n ; and

compare a ratio of total minimum pixel number and total pixel number R with a specification value R s .

33. The apparatus according to claim 26 wherein the means for identifying pixel-level distributions is further configured to:

provide pixel-level distributions of density units D n−1 and D n ;

count an overlap area of the pixel-level distributions of the density units D n−1 and D n ; and

compare the overlap area with a specification value.

34. A method, comprising:

instructing a device to store data associated with an image; and

instructing the device to identify pixel distributions for different distribution elements of the image and use the identified pixel distributions to differentiate the different distribution elements.

35. The method according to claim 34 further comprising instructing the device to use the pixel distributions to exclude interference in the distribution elements induced by image obstacles.

36. The method according to claim 34 further comprising instructing the device to determine which distribution elements are distinguishable or undistinguishable according to an amount of overlap in the pixel distributions between the different distribution elements.