Online wavefront measurement and display

1. A method for centroid detection in an image, comprising:

a) acquiring an X×Y size image represented by a variable pixel signal intensity;

b) compressing the X×Y size image to an X/n×Y/m size image, where n, m equal any integers and X/n, Y/m are integer values;

c) determining a background intensity for any position in the compressed image and subtracting this background from the compressed image;

d) detecting a plurality of approximately positioned centroids in the background-subtracted compressed image;

e) iterating step (d) until approximate positions of a desired plurality of centroids are detected;

f) converting the approximate position of the desired plurality of centroids into more exact positions in the X×Y size image,

whereby every centroid position in the image has been identified;

g) iterating step (f) until a desired level of more exact positions is determined; and

h) assigning a quality factor to each centroid in relation to a magnitude of positional change for each centroid in each iteration of step (g).

2. The method of claim 1 , comprising:

sorting the centroids determined from step (f) according to a predetermined configuration.

3. The method of claim 2 , wherein the configuration is a geometric grid.

4. The method of claim 3 , comprising a rectangular grid.

5. The method of claim 4 , comprising:

a) calculating a straight line formula for each sorted centroid, i, containing the centroid point, i, and having a slope between the values of about <−0.1 or >0.1;

b) calculating a distance, ni, between the line and a reference position in the image;

c) sorting all centroids, in, by ni starting with the smallest ni value;

d) assigning the centroid with the smallest ni to a first row and storing this centroid as a last centroid in the first row;

e) defining a region as an area to the right of a last centroid of a given row having dimensions that are variably controllable by an imaging component parameter and a shape suitable for detection of a selected grid structure;

f) obtaining the next ni value and determining, for all existing rows, whether the centroid is within the region;

g) assigning the centroid as the last centroid in the given row if the centroid is within the region, or, assigning the centroid as the last centroid in a new row if the centroid is outside the region;

h) repeating steps (f-g) for all centroids;

i) calculating an average y-position for each row and sorting the rows according to the average y-positions to identify a top row, Row 1 , a next row, Row 2 , and so on to Row n;

j) assigning the centroid with the smallest ni to a first column and storing this centroid as a last centroid in the first column;

k) defining a region as an area below the last centroid of a given column having dimensions that are variably controllable by the imaging component parameter and a shape suitable for detection of the selected grid structure;

l) obtaining the next ni value and determining, for all existing columns, whether the centroid is within the region;

m) assigning the centroid as the last centroid in the given column if the centroid is within the region, or, assigning the centroid as the last centroid in a new column if the centroid is outside the region;

n) repeating steps (l-m) for all centroids; and

o) calculating an average x-position for each column and sorting the columns according to the average x-positions to identify a first column, Column 1 , a next column, Column 2 , and so on to Column n.

6. The method of claim 5 wherein the reference position is an upper left corner of the image.

7. The method of claim 2 , wherein the configuration is a ring.

8. The method of claim 2 , wherein the configuration is a straight line.

9. The method of claim 2 , comprising:

associating each determined centroid with a respective centroid image forming element.

10. The method of claim 1 , wherein compressing the X×Y size image to an X/n×Y/m size image comprises:

a) averaging the signal for every pixel in an n×m square staffing in a first predetermined region of the original image and scanning through the image, setting a signal level in a corresponding first predetermined region of the compressed image to the average value of the first predetermined region;

b) repeating step (a) for a second and subsequent predetermined regions until the X/n×Y/m image size is obtained.

11. The method of claim 10 , wherein n=m=8.

12. The method of claim 10 , wherein the first predetermined region is the upper left corner of the image.

13. The method of claim 1 , wherein step (c) comprises:

dividing the compressed image into a plurality of image segments each of which contains a plurality of centroids, determining an average signal value for each image segment, and extrapolating the average values for each image segment to determine the background intensity level.

14. The method of claim 13 , wherein the image segments are squares.

15. The method of claim 13 , wherein each image segment contains approximately 3 to 5 centroids.

16. The method of claim 1 , wherein step (d) comprises:

a) determining a maximum signal value in the image;

b) setting a threshold value as a predetermined percentage of the maximum;

c) determining an X-position, a Y-position, and a signal strength of each pixel that has a signal strength greater than the threshold value;

d) sorting the values from step (c) in descending order of signal strength;

e) assigning the highest signal strength as first approximately positioned centroid; and

f) selecting a pre-set condition for defining all sorted values as approximately positioned centroids, which obey the pre-set condition.

17. The method of claim 16 , wherein the pre-set condition is that the position of each subsequent approximately positioned centroid is a farther distance away than a pre-set distance from all yet determined approximately positioned centroids.

18. The method of claim 17 , further comprising setting a new threshold value to a predetermined percentage of a minimum value of the sorted signal strengths and iterating steps (c-f), wherein the already identified approximately positioned centroids are not identified again.

19. The method of claim 1 , wherein step (I) comprises:

defining a boundary structure around every approximate position of the desired plurality of centroids in the original image; and

determining a center of mass of the signal for the signal distribution inside of the boundary.

20. A device readable medium having stored thereon an executable instruction in the form of the method of claim 1 .