Selective processing of anomalous pixels systems and methods

Patent metadata

Field	Value
Publication number	US-11915394-B2
Application number	US-202217725502-A
Country	US
Kind code	B2
Filing date	Apr 20, 2022
Priority date	May 11, 2021
Publication date	Feb 27, 2024
Grant date	Feb 27, 2024

Abstract

Techniques are provided to identify, correct, and/or replace anomalous pixels. In one example, a method includes receiving an image frame comprising a plurality of pixels arranged in a plurality of rows and columns. The pixels comprise image data associated with a scene and fixed pattern noise introduced by an imaging device. The method also includes performing a first process on a first set of the pixels to determine associated correction terms configured to reduce the fixed pattern noise, and applying the correction terms to the first set of the pixels in response to the first process. The method also includes performing a second process on a second set of the pixels to determine whether to replace the second set of the pixels to reduce the fixed pattern noise, and replacing at least a subset of the second set of the pixels in response to the second process. Additional methods and systems are also provided.

First claim

What is claimed is:

1. A method comprising:
receiving an image frame comprising a plurality of pixels arranged in a plurality of rows and columns, wherein the pixels comprise image data associated with a scene and fixed pattern noise introduced by an imaging system;
detecting whether motion is present at the imaging system;
if motion is detected, performing a first process to determine a correction term configured to reduce the fixed pattern noise for a selected one of the pixels, wherein the first process comprises comparing the selected pixel to a plurality of neighbor pixels of a first kernel;
if motion is not detected, performing a second process to determine whether to replace the selected pixel to reduce the fixed pattern noise, wherein the second process comprises determining a plurality of linearity measurements based on the selected pixel and a plurality of neighbor pixels of a second kernel; and
applying the correction term to the selected pixel in response to the first process or replacing the selected pixel in response to the second process.

2. The method of claim 1 , wherein the first process comprises:
adjusting a counter in response to the comparing; and
adjusting the correction term associated with the selected pixel in response to the counter.

3. The method of claim 2 , further comprising:
limiting the correction term to a maximum correction term.

4. The method of claim 1 , further comprising:
performing the second process if the correction term exceeds a maximum correction term, regardless of whether motion is detected.

5. The method of claim 1 , wherein the second process comprises:
identifying the selected pixel as anomalous in response to the linearity measurements.

6. The method of claim 5 , further comprising:
updating a spatial anomaly score based on the linearity measurements; and
the identifying comprises comparing the spatial anomaly score to a spatial anomaly score threshold.

7. The method of claim 5 , wherein the determining comprises:
calculating a plurality of estimated values for the selected pixel using a plurality of corresponding subsets of the neighbor pixels of the second kernel; and
comparing the estimated values to one or more linearity threshold values to determine the linearity measurements.

8. The method of claim 5 , wherein the determining comprises:
identifying a plurality of vectors each comprising the selected pixel and a corresponding subset of the neighbor pixels of the second kernel;
for each vector, calculating an estimated value of the selected pixel using the corresponding subset of the neighbor pixels of the second kernel; and
comparing the estimated values to one or more linearity threshold values to determine the linearity measurements.

9. The method of claim 1 , wherein at least a subset of the first kernel overlaps with at least a subset of the second kernel.

10. The method of claim 1 , further comprising repeating the method for a plurality of image frames, wherein the image frames are thermal image frames and the imaging system is a thermal camera.

11. A system comprising:
an imager configured to capture an image frame comprising a plurality of pixels arranged in a plurality of rows and columns, wherein the pixels comprise image data associated with a scene and fixed pattern noise introduced by the system; and
a logic device configured to:
detect whether motion is present at the imaging system,
if motion is detected, perform a first process to determine a correction term configured to reduce the fixed pattern noise for a selected one of the pixels, wherein the first process comprises comparing the selected pixel to a plurality of neighbor pixels of a first kernel,
if motion is not detected, perform a second process to determine whether to replace the selected pixel to reduce the fixed pattern noise, wherein the second process comprises determining a plurality of linearity measurements based on the selected pixel and a plurality of neighbor pixels of a second kernel, and
apply the correction term to the selected pixel in response to the first process or replace the selected pixel in response to the second process.

12. The system of claim 11 , wherein the first process comprises:
adjusting a counter in response to the comparing; and
adjusting the correction term associated with the selected pixel in response to the counter.

13. The system of claim 12 , wherein the logic device is configured to:
limit the correction term to a maximum correction term.

14. The system of claim 11 , wherein:
the logic device is configured to perform the second process if the correction term exceeds a maximum correction term, regardless of whether motion is detected.

15. The system of claim 11 , wherein the second process comprises:
identifying the selected pixel as anomalous in response to the linearity measurements.

16. The system of claim 15 , wherein the logic device is configured to:
update a spatial anomaly score based on the linearity measurements; and
compare the spatial anomaly score to a spatial anomaly score threshold to identify the selected pixel as anomalous.

17. The system of claim 15 , wherein the logic device is configured to:
calculate a plurality of estimated values for the selected pixel using a plurality of corresponding subsets of the neighbor pixels; and
compare the estimated values to one or more linearity threshold values to determine the linearity measurements.

18. The system of claim 15 , wherein the logic device is configured to:
identify a plurality of vectors each comprising the selected pixel and a corresponding subset of the neighbor pixels;
for each vector, calculate an estimated value of the selected pixel using the corresponding subset of the neighbor pixels; and
compare the estimated values to one or more linearity threshold values to determine the linearity measurements.

19. The system of claim 11 , wherein at least a portion of the first set of the pixels overlaps with at least a portion of the second set of the pixels.

20. The system of claim 11 , wherein the logic device is configured to perform the first process and the second process for a plurality of image frames, the imager is a thermal imager, the image frames are thermal image frames, and the system is a thermal camera.

Assignees

• Teledyne Flir Commercial Systems Inc

Inventors

• Moreira Julie R
• Lin Stephanie

Classifications

• G06T3/4053

  based on super-resolution, i.e. the output image resolution being higher than the sensor resolution · CPC title

• G06T2207/10048

  Infrared image · CPC title

• H04N23/80

  Camera processing pipelines; Components thereof · CPC title

• G06T2207/30168

  Image quality inspection · CPC title

• G06T2207/20201

  Motion blur correction · CPC title