Ditherless non-uniformity compensation for infrared detector arrays with recursive spatial low pass filtering

• US 20010042825A1
• Filed: 02/16/2001
• Published: 11/22/2001
• Est. Priority Date: 08/30/1996
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Young, Ching-ju J.
• Granted Patent: US 6,507,018 B2
• Time in Patent Office: Days
• US Class Current: 250/252.1
• CPC Class Codes: H04N 23/81 for suppressing or minimising disturbance in the image signal generation
• CPC Class Codes: H04N 25/63 applied to dark current
• CPC Class Codes: H04N 25/674 based on the scene itself, e.g. defocusing
• CPC Class Codes: H04N 5/33 Transforming infrared radiation cameras or camera modules for generating image signals from infrared radiation H04N23/20; circuitry of SSIS for transforming infrared radiation into image signals H04N25/20

Abstract

A non-dither spatio-temporal low pass filter method for compensating non-uniformity of the responses of detector elements of an infrared detector array. The methods can be used for one-dimensional scanning arrays and for two-dimensional staring arrays. (FIGS. 3 and 6). First it is determined whether the scene and the detector array have sufficient relative motion for use of a spatio-temporal low pass filter type non-uniformity compensation (NUC) algorithm. If so the NUC algorithm is applied, which recursively uses both spatial and temporal information from near neighbors as a basis to correct fixed pattern noise on the detector array.

Claims

1. A ditherless method of compensating non-uniformities among detector elements of an infrared detector array that captures images of a scene, where each detector element of the array has at least one neighbor, comprising the steps of:

determining whether there is relative motion of at least a portion of the scene and the detector array;

if there is relative motion, performing a non-uniformity compensation process as follows;

receiving two sets of output values, each set representing two matrices of output data from said array, the sets being from a first field and a second field detected by the array at different times;

applying any previously calculated offset correction values to the output values;

for the first field, subtracting output values of neighbors in a first direction from detector element values;

for the second field, subtracting output values of neighbors in a second direction from detector element values;

adding the results of the two subtracting steps;

“

dividing”

the sum by four, thereby obtaining new offset correction values;

updating any previously calculated offset correction values with the new offset correction values; and

repeating the above steps for a desired number of iterations.

2. The method of

claim 1

, wherein the first direction and the second direction are up and down.

3. The method of

claim 1

, wherein the first direction and the second direction are left and right.

4. The method of

claim 1

, wherein the method is performed for a one dimensional array and the images are successive columns of the array.

5. The method of

claim 1

, wherein the method is performed for a two-dimensional array, and further comprising the steps of repeating the subtracting, adding and dividing steps for a second dimension in directions orthogonal to those for a first dimension.

6. The method of

claim 1

, further comprising the step of determining if the relative motion exceeds a threshold.

7. The method of

claim 1

, further comprising the step of using local scene data to locally limit application of the method.

8. The method of

claim 1

, wherein the step of determining whether there is relative motion is performed by differencing two fields of the scene.

9. The method of

claim 1

, wherein the step of determining whether there is relative motion is performed by determining at least one partial area of motion.

10. The method of

claim 1

, wherein the step of determining whether there is relative motion is performed by determining global motion.

11. The method of

claim 1

, further comprising the step of compensating for non-uniform gain.

12. The method of

claim 1

, wherein the non-uniformity compensation process further comprises the step of applying a weighting factor operable to slow convergence of the compensation process.

13. A ditherless method of compensating non-uniformities among detector elements of an infrared detector array that captures images of a scene, where each detector element of the array has at least one neighbor, comprising the steps of:

determining whether there is relative motion of the at least a portion of the scene and the detector array;

if there is relative motion, performing a non-uniformity compensation process as follows;

receiving two sets of output values, each set representing two matrices of output data from said array, the sets being from a first field and a second field detected by the array at different times;

applying any previously calculated offset correction values to the output values;

calculating first new offset correction values by performing the following operations for each detector element;

averaging an output value of at least one first neighbor and an output value of that detector element, and subtracting the average from the output value of that detector element;

correcting said output values with said first new offset correction values;

calculating second new offset correction values by performing the following operations for each detector element;

averaging an output value of at least one second neighbor and an output value of that detector element, and subtracting the average from the output value of that detector element;

updating any previously calculated offset correction values with the first new offset correction values and the second new offset correction values; and

repeating the above steps for a desired number of iterations.

14. The method of

claim 13

, wherein said calculating steps are further performed by including output values from one or more additional neighbors in said averaging.

15. The method of

claim 13

, wherein said steps are repeated until said second new offset correction values become substantially constant.

16. The method of

claim 13

, wherein said array is a one-dimensional scanning array and said receiving step is performed such that said fields are dithered in the cross-direction of the scanning direction of said array.

17. The method of

claim 13

, wherein said array is a two-dimensional array and further comprising the steps of repeating the calculating and correcting steps for a second dimension in directions orthogonal to those for a first dimension.

18. The method of

claim 13

, wherein said calculating steps are performed with an even number of neighbors, said neighbors forming a symmetrical pattern with respect to that detector element.

19. The method of

claim 13

, further comprising the step of determining if the relative motion exceeds a threshold.

20. The method of

claim 13

, wherein the step of determining whether there is relative motion is performed by differencing two fields of the scene.

21. The method of

claim 13

, wherein the step of determining whether there is relative motion is performed by determining at least one partial area of motion.

22. The method of

claim 13

, wherein the step of determining whether there is relative motion is performed by determining global motion.

23. The method of

claim 13

, further comprising the step of compensating for non-uniform gain.

24. The method of

claim 13

, wherein the non-uniformity compensation process further comprises the step of applying a weighting factor operable to slow convergence of the compensation process.

29. The system of

claim 23

, wherein the motion detection process is performed by determining if the relative motion exceeds a threshold.

25. An infrared detector system for providing images of a scene without dithering, comprising:

a detector having an array of detector elements;

an analog to digital converter associated with each detector element; and

a processing system programmed to receive data from the analog to digital converters and to process the data to provide an infrared image, the processing using a motion detection process that detects whether there is relative motion between at least a portion of the scene and the detector array, and a non-uniformity compensation (NUC) process that implements a spatial low pass filter and uses temporarily shifted data from near neighbor detector elements in a bi-directional pattern.

26. The system of

claim 25

, wherein the NUC algorithm is an orthogonal algorithm.

27. The system of

claim 25

, wherein the NUC algorithm is a one-dimensional algorithm.

28. The system of

claim 25

, wherein the NUC algoritym is a two-dimensional algorithm.

30. The system of

claim 25

, wherein the motion detection process is performed by differencing two fields of the scene.

31. The system of

claim 25

, wherein the motion detection process is performed by determining at least one local area of motion.

32. The system of

claim 25

, wherein the step of determining whether there is relative motion is performed by determining global motion.

33. The system of

claim 25

, wherein the NUC process compensates for both offset and gain non-uniformity.

34. The system of

claim 25

, wherein the non-uniformity compensation process further comprises the step of applying a weighting factor operable to slow convergence of the compensation process.

35. A ditherless method of compensating non-uniformities among detector elements of an infrared detector array that captures images of a scene, where each detector element of the array has at least one neighbor, comprising the steps of:

determining whether there is relative motion of at least a portion of the scene and the detector array; and

if there is relative motion, performing a non-uniformity compensation process as follows;

receiving at least two sets of output values, each set representing two matrices of output values from the array, the sets being from different fields detected by the array at different times;

applying any calculated offset correction values to the output values;

calculating new offset correction values for each detector element by using a value from that detector element and values from its bi-directional neighbors to implement a mathematical spatial low pass filter;

updating any previously calculated offset correction values with the new offset correction values; and

repeating the above steps for a desired number of iterations.

36. The method of

claim 35

v, wherein the bi-directional neighbors are up and down.

37. The method of

claim 35

, wherein the bi-directional neighbors are left and right.

38. The method of

claim 35

, wherein the bi-directional neighbors are diagonal.

39. The method of

claim 35

, wherein the method is performed for a one dimensional array and the images are successive columns of the array.

40. The method of

claim 35

, wherein the method is performed for two-dimensional array, and further comprising the steps of repeating the subtracting, adding and dividing steps for a second dimension in directions orthogonal to those for a first dimension.

41. The method of

claim 35

, further comprising the step of determining if the relative motion exceeds a threshold.

42. The method of

claim 35

, further comprising the step of using local scene data to locally limit application of the method.

43. The method of

claim 35

, wherein the step of determining whether there is relative motion is performed by differencing two fields of the scene.

44. The method of

claim 35

, wherein the step of determining whether there is relative motion is performed by determining at least one local area of motion.

45. The method of

claim 35

, wherein the step of determining whether there is relative motion is performed by determining global motion.

46. The method of

claim 35

, further comprising the step of compensating for non-uniform gain.

47. The method of

claim 35

, wherein the non-uniformity compensation process further comprises the step of applying a weighting factor operable to slow convergence of the compensation process.