Imagers having image processing circuitry with error detection capabilities

• US 9,531,968 B2
• Filed: 02/25/2014
• Issued: 12/27/2016
• Est. Priority Date: 02/25/2014
• Status: Active Grant

• Current Assignee: Semiconductor Components Industries LLC (ON Semiconductor Corporation)
• Original Assignee: Semiconductor Components Industries LLC (ON Semiconductor Corporation)
• Inventors: Boorom, Kenneth Fiske
• Primary Examiner(s): KHAN, USMAN A
• Application Number:
  US14/189,939
• Publication Number:
  US 20150244948A1
• Time in Patent Office: 1,036 Days
• Field of Search: 348/241
• US Class Current: 1/1
• CPC Class Codes: H04N 25/60 Noise processing, e.g. detecting, correcting, reducing or removing noise
• CPC Class Codes: H04N 25/76 Addressed sensors, e.g. MOS or CMOS sensors

Abstract

Image processing circuitry may be used to detect imaging errors of a pixel array, including imaging errors that would otherwise be difficult to detect visually. The image processing circuitry may identify a subset of the pixels that are characterized by burst noise such as RTS noise. The image processing circuitry may monitor the identified subset of the pixels to detect imaging errors. The circuitry may maintain histograms of image values for the subset of pixels from previously captured images. The image processing circuitry may update the histograms using each new captured image and determine whether the updated histograms have tri-modal distributions. In response to determining that the updated histograms do not have tri-modal distributions of values, the circuitry may identify that an imaging error has occurred. If desired, expected differences in dark current across multiple exposure settings may be used to help identify imaging errors.

Claims

1. A method of using image processing circuitry to detect imaging errors of a pixel array having a plurality of pixels, the method comprising:

with the image processing circuitry, identifying a subset of the pixels of the pixel array that are characterized by noise; and

monitoring the identified subset of the pixels to detect imaging errors, wherein monitoring the identified subset of the pixels comprises maintaining a histogram of captured image values for a single given pixel of the subset of the pixels based on previously captured images, and wherein maintaining the histogram of captured image values comprises maintaining a count of a number of occurrences of each of the captured image values.

2. The method defined in claim 1 wherein monitoring the identified subset of the pixels to detect imaging errors further comprises:

capturing an image using the pixel array;

updating the histogram for the given pixel using the captured image; and

determining whether the updated histogram has a tri-modal distribution.

3. The method defined in claim 2 wherein monitoring the identified subset of the pixels to detect imaging errors further comprises:

in response to determining that the updated histogram does not have a tri-modal distribution, identifying that an imaging error has occurred.

4. The method defined in claim 2 wherein monitoring the identified subset of the pixels to detect imaging errors further comprises:

in response to determining that the updated histogram has a tri-modal distribution, capturing additional images with the pixel array.

5. The method defined in claim 3 wherein identifying the subset of the pixels that are characterized by noise comprises:

capturing a sequence of test images with the pixel array; and

comparing the captured test images to identify the subset of the pixels that are characterized by noise.

6. The method defined in claim 5 wherein capturing the sequence of test images comprises capturing a sequence of gray test images.

7. The method defined in claim 6 wherein identifying the subset of the pixels that are characterized by noise further comprises:

for each pixel, determining whether pixel values produced by that pixel have a tri-modal distribution across the captured test images and, in response to determining that the pixel values produced by that pixel have the tri-modal distribution across the captured test images, assigning that pixel to the subset of pixels that are characterized by noise.

8. The method defined in claim 7 wherein assigning that pixel to the subset of pixels that are characterized by noise comprises identifying a location of that pixel within the pixel array.

9. The method defined in claim 3 wherein each pixel comprises a photodiode that is coupled to a source-follower transistor by a transfer gate and wherein identifying the subset of the pixels that are characterized by noise comprises:

identifying pixels that have been fabricated with charge traps at the source-follower transistor.

10. The method defined in claim 1 further comprising:

with the pixel array, capturing a first image with a first exposure length;

with the pixel array, capturing a second image with a second exposure length;

calculating differences between captured image values of the first and second captured images;

determining whether the calculated differences are consistent with expected difference values; and

in response to determining that the calculated differences are not consistent with the expected difference values, identifying that an imaging error has occurred.

11. The method defined in claim 1, wherein the histogram of captured image values for a single given pixel is based on pixel reset signals for the single given pixel.

12. A method of detecting imaging errors, the method comprising:

with a pixel array, capturing a first image of a given scene with a first exposure length;

with the pixel array, capturing a second image of the given scene with a second exposure length;

identifying a current operating temperature of the pixel array;

identifying a first expected dark current value for the first exposure length based on the current operating temperature;

identifying a second expected dark current value for the second exposure length based on the current operating temperature;

with image processing circuitry, calculating an expected dark current difference by subtracting the first expected dark current value from the second expected dark current value; and

with the image processing circuitry, determining whether differences in the first and second captured images match the expected dark current difference.

13. The method defined in claim 12 wherein determining whether the differences in the first and second captured images match the expected dark current difference comprises:

with the image processing circuitry, computing the expected differences in the first and second captured images based on the difference in expected dark current between the first exposure length and the second exposure length.

14. The method defined in claim 12 wherein the pixel array comprises an active region and an inactive region, wherein capturing the first image of the given scene with the first exposure length with the pixel array comprises capturing the first image using only pixels of the inactive region, and wherein capturing the second image of the given scene with the second exposure length with the pixel array comprises capturing the second image using only the pixels of the inactive region.

15. A system, comprising:

a central processing unit;

memory;

input-output circuitry; and

an imaging device, wherein the imaging device comprises;

a pixel array;

a lens that focuses an image on the pixel array; and

image processing circuitry that identifies a subset of the pixels of the pixel array that are characterized by noise and monitors the identified subset of the pixels to detect imaging errors, wherein monitoring the identified subset of the pixel to detect imaging errors comprises maintaining a first histogram of pixel values for only a first given pixel of the identified subset and maintaining a second histogram of pixel values for only a second given pixel of the identified subset, and wherein the pixel values comprise captured pixel image signals.

16. The system defined in claim 15 wherein the pixel array comprises:

a semiconductor substrate;

a first plurality of pixels; and

a second plurality of pixels that comprises the identified subset of pixels, wherein the second plurality of pixels are different from the first plurality of pixels and wherein each pixel of the second plurality of pixels includes fabricated charge traps.

17. The system defined in claim 16 wherein each pixel of the pixel array comprises:

a photodiode;

a transfer gate that couples the photodiode to a floating diffusion region; and

a source-follower transistor having a gate terminal that is coupled to the floating diffusion region, wherein the fabricated charge traps are at the gate terminal.

18. The system defined in claim 17 wherein the source-follower transistor comprises:

an oxide layer deposited on the semiconductor substrate;

source and drain regions in the semiconductor substrate; and

a gate layer on the oxide layer, wherein the gate layer is doped with impurities to form the charge traps.

19. The system defined in claim 15 wherein the image processing circuitry detects imaging errors based on whether the histograms of pixel values have tri-modal distributions.

20. The system defined in claim 15 wherein the pixel values comprise correlated double sampling pixel output signals, wherein the correlated double sampling pixel output signals are based on the captured pixel image signals and pixel reset signals.