Non-uniformity correction (NUC) self-calibration using images obtained using multiple respective global gain settings
A non-uniformity correction (NUC) calibration method comprises obtaining image data for a plurality of images with an image sensor, wherein each image in the plurality of images is obtained at a different respective global pixel gain setting and global expose in the image sensor; and using the image data for non-uniformity correction calibration to compute pixel NUC values for the pixels in the image sensor. The method can further include storing the pixel NUC values and obtaining further image data corrected by the stored pixel NUC values. In embodiments, the method can include moving a platform based on the further image data. In certain embodiments, the platform can be a guided munition.
1. A non-uniformity correction (NUC) calibration method comprising:
obtaining image data for a plurality of images with an image sensor, wherein each image in the plurality of images is obtained at a different respective global pixel gain setting in the image sensor;
using the image data for non-uniformity correction to compute pixel NUC values for the pixels in the image sensor;
storing the pixel NUC values;
obtaining further image data corrected by the stored Pixel NUC values;
moving a platform based on the further image data, wherein the platform is a guided munition, wherein obtaining image data and using the image data for non-uniformity correction calibration are performed onboard a guided munition seeker while the guided munition seeker is in transit and actively seeking a target.
2. The method as recited in claim 1 , wherein the NUC calibration is performed using images obtained with an imaging device onboard the guided munition seeker without any darkening of an optical path through the imaging device.
3. The method as recited in claim 1 , wherein obtaining image data further includes a performing a control algorithm, the control algorithm including:
setting a readout integrated circuit global control to a respective gain or expose duration setting before each image is obtained; and
storing to a memory pixel values for each obtained image with the respective gain setting.
4. The method as recited in claim 3 , wherein the control algorithm further includes increasing the respective gain and/or exposure time setting; and
storing to memory pixel values for each obtained image with the increased respective gain setting.
5. The method as recited in claim 4 , wherein the control algorithm further includes increasing the respective gain and/or exposure time setting; and
storing to memory pixel values for each obtained image with each subsequent increased respective gain setting until maximum gain setting is reached, wherein maximum gain is reached when noise saturates pixels A/D value.
6. The method as recited in claim 5 , wherein the method further includes performing the control algorithm for 11 levels of illumination.
7. The method as recited in claim 1 , wherein using the image data for non-uniformity correction includes performing a process pixel data algorithm, the process pixel data algorithm including:
computing a noise floor at a zero gain setting;
obtaining a frame average of all pixels at zero gain setting; and
computing a respective pixel's zero gain bias correction by calculating a difference between pixel average value and frame average value.
8. The method as recited in claim 7 , wherein the process pixel data algorithm further includes zero bias correcting all collected pixel data.
9. The method as recited in claim 8 , wherein the process pixel data algorithm further includes:
computing de-speckle pixel correction values on all pixel zero bias corrected pixel data; and
ignoring saturated pixels.
10. The method as recited in claim 9 , wherein the process pixel data algorithm further includes computing bias and scale factor linear fit values between de-speckle correction values and pixel value from all respective gain settings.
11. The method as recited in claim 9 , wherein the process pixel data algorithm further includes storing the zero bias, fitted bias, and scale factor values as NUC correction values for each pixel in the obtained image.
12. The method as recited in claim 11 , wherein the method further includes performing the process pixel data algorithm for 11 levels of illumination.
13. A non-uniformity correction (NUC) calibration method comprising:
obtaining image data for a plurality of images with an image sensor, wherein each image in the plurality of images is obtained at a different respective global pixel gain setting in the image sensor; and
using the image data for non-uniformity correction to compute pixel NUC values for the pixels in the image sensor,
wherein obtaining image data further includes a performing a control algorithm, the control algorithm including:
setting a readout integrated circuit global control to a respective gain or expose duration setting before each image is obtained;
storing to a memory pixel values for each obtained image with the respective gain setting;
increasing the respective gain and/or exposure time setting;
storing to memory pixel values for each obtained image with the increased respective gain setting;
increasing the respective gain and/or exposure time setting; and
storing to memory pixel values for each obtained image with each subsequent increased respective gain setting until maximum gain setting is reached, wherein maximum gain is reached when noise saturates pixels A/D value.
14. The method as recited in claim 13 , wherein the method further includes performing the control algorithm for 11 levels of illumination.
15. A non-uniformity correction (NUC) calibration method comprising:
obtaining image data for a plurality of images with an image sensor, wherein each image in the plurality of images is obtained at a different respective global pixel gain setting in the image sensor; and
using the image data for non-uniformity correction to compute pixel NUC values for the pixels in the image sensor, wherein using the image data for non-uniformity correction includes performing a process pixel data algorithm, the process pixel data algorithm including:
computing a noise floor at a zero gain setting;
obtaining a frame average of all pixels at zero gain setting; and
computing a respective pixel's zero gain bias correction by calculating a difference between pixel average value and frame average value.
16. The method as recited in claim 15 , wherein the process pixel data algorithm further includes zero bias correcting all collected pixel data.
17. The method as recited in claim 16 , wherein the process pixel data algorithm further includes:
computing de-speckle pixel correction values on all pixel zero bias corrected pixel data; and
ignoring saturated pixels.
18. The method as recited in claim 17 , wherein the process pixel data algorithm further includes computing bias and scale factor linear fit values between de-speckle correction values and pixel value from all respective gain settings.
19. The method as recited in claim 17 , wherein the process pixel data algorithm further includes storing the zero bias, fitted bias, and scale factor values as NUC correction values for each pixel in the obtained image.