Adaptive non-uniformity compensation algorithm

• US 5,903,659 A
• Filed: 04/17/1997
• Issued: 05/11/1999
• Est. Priority Date: 04/17/1997
• Status: Expired due to Term

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Kilgore, Patrick M.
• Primary Examiner(s): ROGERS, SCOTT A
• Application Number:
  US08/843,874
• Time in Patent Office: 754 Days
• Field of Search: 382/103, 382/218, 382/255, 382/263, 382/264, 382/262, 382/261, 382/260, 382/275, 382/254, 382/266, 382/269, 382/106, 348/169, 348/607, 348/241, 348/252, 348/625, 348/345, 348/348, 250/347, 250/332, 250/208.1
• US Class Current: 382/103
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: H04N 23/20 for generating image signals from infrared radiation only
• 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

An adaptive method for removing fixed pattern noise from focal plane array (FPA) imagery. A set of correction terms is applied to the focused image from the FPA, and a filter is applied to the corrected, focused image. The set of correction terms is also applied to a blurred version of the FPA image, and the filter is applied to the corrected, blurred image. Fixed pattern noise errors are then calculated using the filtered imagery, and employed to update the correction terms. The updated correction terms are then used for processing the next image. In one embodiment, the filter is an anti-median filter. In another embodiment, the filter is an anti-mean filter.

Claims

1. An adaptive method for removing fixed pattern noise from focal plane array (FPA) imagery, comprising the following steps:

obtaining respective focused and blurred digitized versions of an FPA image;

applying a set of correction terms to the focused version of said FPA image to provide a corrected, focused FPA image;

applying a filter to the corrected, focused version of said FPA image to obtain a filter focus image;

applying said set of correction terms to said blurred version of the FPA image to provide a corrected, blurred version of said FPA image;

applying said filter to the corrected, blurred image to provide a filter blur image;

calculating fixed pattern noise errors using the filter focus image and the filter blur image; and

employing said fixed pattern noise errors to update the correction terms for use in processing a next FPA image.

2. The method of claim 1 wherein said filter includes an anti-median filter which provides, for each pixel in an image, a corresponding anti-median value which is a measure of how the pixel differs from a median value of the pixel and a set of neighboring pixels.

3. The method of claim 2 wherein said set of neighboring pixels includes two pixels on opposite sides of the pixel whose median value is to be calculated.

4. The method of claim 3 wherein said step of calculating said errors includes adding boundary rows and columns of pixels values of alternating maximum and minimum pixels values to said corrected output image to bound said output image and accommodate boundary conditions.

5. The method of claim 2 wherein said step of calculating said errors includes comparing corresponding values of said focus and blur images, and calculating a corresponding error term in dependence on said comparison.

6. The method of claim 1 wherein said filter includes an anti-mean filter which provides, for each pixel in an image, a corresponding anti-mean value which is a measure of how the pixel differs from a mean value of the pixel and a set of neighboring pixels.

7. The method of claim 6 wherein said set of neighboring pixels includes a group of neighboring pixels, and wherein pixels in said group having maximum and minimum values are excluded from calculation of said mean value.

8. The method of claim 6 wherein said step of calculating said errors includes comparing corresponding values of said focus and blur images, and calculating a corresponding error term in dependence on said comparison.

9. The method of claim 1 wherein said FPA image is an infrared image.

10. An adaptive sensor and non-uniformity compensation system for providing a corrected output image from a focal plane array (FPA), wherein fixed pattern noise has been compensated in FPA imagery, comprising:

a sensor comprising sensor optics, a focal plane array of infrared detectors for producing FPA images, and analog-to-digital conversion apparatus for converting said FPA images into digitized FPA images comprising a set of pixel values, the sensor optics adapted to provide focused and blurred versions of images;

an adaptive non-uniformity compensation processor for compensating for non-uniform sensitivities of said infrared detectors to infrared radiation, said processor adjusting each pixel value to compensate for the differing sensitivity of each detector in the FPA and provide a corrected output image, said processor comprising;

first means for applying a set of correction terms to a focused version of said FPA image to provide a corrected, focused FPA image;

a first filter system for applying a filter to the corrected, focused version of said FPA image to obtain a filter focus image;

second means for applying said set of correction terms to said blurred version of the FPA image to provide a corrected, blurred version of said FPA image;

a second filter system for applying said filter to the corrected, blurred image to provide a filter blur image;

third means for calculating fixed pattern noise errors using the filter focus image and the filter blur image; and

fourth means for employing said fixed pattern noise errors to update the correction terms for use in processing a next FPA image.

11. The system of claim 10 wherein said filter includes an anti-median filter which provides, for each pixel in an image, a corresponding anti-median value which is a measure of how the pixel differs from a median value of the pixel and a set of neighboring pixels.

12. The system of claim 11 wherein said set of neighboring pixels includes two pixels on opposite sides of the pixel whose median value is to be calculated.

13. The system of claim 11 wherein said third means for calculating said errors includes means for comparing corresponding values of said focus and blur images, and means for calculating a corresponding error term in dependence on said comparison.

14. The system of claim 10 wherein said filter includes an anti-mean filter which provides, for each pixel in an image, a corresponding anti-mean value which is a measure of how the pixel differs from a mean value of the pixel and a set of neighboring pixels.

15. The system of claim 14 wherein said set of neighboring pixels includes a group of neighboring pixels, and wherein pixels in said group having maximum and minimum values are excluded from calculation of said mean value.

16. The system of claim 13 wherein said third means for calculating said errors includes means for comparing corresponding values of said focus and blur images, and means for calculating a corresponding error term in dependence on said comparison.