Systems and methods for processing infrared images

• US 9,237,284 B2
• Filed: 09/18/2012
• Issued: 01/12/2016
• Est. Priority Date: 03/02/2009
• Status: Active Grant

• Current Assignee: Teledyne FLIR LLC (Teledyne Technologies Incorporated)
• Original Assignee: FLIR Systems, Inc. (Teledyne Technologies Incorporated)
• Inventors: Hgasten, Nicholas, Ingerhed, Malin
• Primary Examiner(s): Park, Chan
• Assistant Examiner(s): Summers, Geoffrey E
• Application Number:
  US13/622,178
• Publication Number:
  US 20130022279A1
• Time in Patent Office: 1,211 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: H04N 25/677 for reducing the column or line fixed pattern noise
• 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

Various techniques are provided to process infrared images. In one implementation, a method of processing infrared image data includes receiving infrared image data associated with a scene. The infrared image data comprises a plurality of pixels arranged in a plurality of rows and columns. The method also includes selecting one of the columns. The method also includes, for each pixel of the selected column, comparing the pixel to a corresponding plurality of neighborhood pixels. The method also includes, for each comparison, adjusting a first counter if the pixel of the selected column has a value greater than the compared neighborhood pixel. The method also includes, for each comparison, adjusting a second counter if the pixel of the selected column has a value less than the compared neighborhood pixel. The method also includes selectively updating a column correction term associated with the selected column based on the first and second counters.

Claims

1. A method of processing infrared image data, the method comprising:

receiving infrared image data associated with a scene, wherein the infrared image data comprises a plurality of pixels arranged in a plurality of rows and columns, wherein at least a subset of the pixels comprise column noise;

selecting one of the columns;

for each pixel of the selected column, comparing the pixel to a corresponding plurality of neighborhood pixels residing in the same row as the pixel;

for each comparison, adjusting a first counter if the pixel of the selected column has a value greater than the compared neighborhood pixel;

for each comparison, adjusting a second counter if the pixel of the selected column has a value less than the compared neighborhood pixel;

for each comparison, adjusting a third counter if the pixel of the selected column has a value equal to the compared neighborhood pixel;

determining, based on at least the first, second, and third counters, that an update condition for a column correction term associated with the selected column is met; and

selectively updating the column correction term in response to the determining that the update condition is met to reduce the column noise associated with the selected column.

2. The method of claim 1, wherein the updating comprises:

performing one or more calculations using values of, at least, the first and second counters;

adjusting the column correction term if the one or more calculations indicate that the values of the pixels of the selected column are associated with column noise; and

refraining from adjusting the column correction term if the one or more calculations indicate that the values of the pixels of the selected column are associated with an object in the scene.

3. The method of claim 1, wherein the first and second counters are implemented by registers, memory locations, or accumulators.

4. The method of claim 1, wherein the neighborhood pixels corresponding to each pixel of the selected column reside in a neighborhood defined by an intersection of:

the same row as the pixel of the selected column; and

a predetermined range of columns.

5. The method of claim 4, wherein the neighborhood has a range of at least two columns, wherein the infrared image data comprises 512 rows and 640 columns.

6. The method of claim 1, further comprising performing the selecting, comparing, adjusting, and updating for all remaining columns of the infrared image data.

7. The method of claim 1, wherein the infrared image data is first infrared image data, the method further comprising:

receiving second infrared image data;

applying the updated column correction term to the second infrared image data to provide second corrected infrared image data; and

performing the selecting, comparing, adjusting, and updating using the second corrected infrared image data to further update the column correction term.

8. The method of claim 1, further comprising:

applying the updated column correction term to the infrared image data to provide corrected infrared image data; and

repeating the comparing, adjusting, and updating for the selected column using the corrected infrared image data.

9. The method of claim 1, wherein the first and second counters are first and second column-based processing counters, wherein the neighborhood pixels are first neighborhood pixels, the method further comprising:

selecting one of the rows;

for each pixel of the selected row, comparing the pixel to a corresponding plurality of second neighborhood pixels;

for each comparison, adjusting a first row-based processing counter if the pixel of the selected row has a value greater than the compared second neighborhood pixel;

for each comparison, adjusting a second row-based processing counter if the pixel of the selected row has a value less than the compared second neighborhood pixel; and

selectively updating a row correction term associated with the selected row based on the first and second row-based processing counters.

10. A system comprising:

a memory component adapted to receive infrared image data associated with a scene, wherein the infrared image data comprises a plurality of pixels arranged in a plurality of rows and columns, wherein at least a subset of the pixels comprise column noise; and

a processor adapted to execute instructions to;

select one of the columns,

for each pixel of the selected column, compare the pixel to a corresponding plurality of neighborhood pixels residing in the same row as the pixel,

for each comparison, adjust a first counter if the pixel of the selected column has a value greater than the compared neighborhood pixel,

for each comparison, adjust a second counter if the pixel of the selected column has a value less than the compared neighborhood pixel,

for each comparison, adjust a third counter if the pixel of the selected column has a value equal to the compared neighborhood pixel;

determine, based on at least the first, second, and third counters, that an update condition for a column correction term associated with the selected column is met; and

selectively update the column correction term in response to the determining that the update condition is met to reduce the column noise associated with the selected column.

11. The system of claim 10, wherein the instructions to update the column correction term are adapted to cause the processor to:

perform one or more calculations using values of, at least, the first and second counters;

adjust the column correction term if the one or more calculations indicate that the values of the pixels of the selected column are associated with column noise; and

refrain from adjusting the column correction term if the one or more calculations indicate that the values of the pixels of the selected column are associated with an object in the scene.

12. The system of claim 10, wherein the first and second counters are implemented by registers, memory locations, or accumulators.

13. The system of claim 10, wherein the neighborhood pixels corresponding to each pixel of the selected column reside in a neighborhood defined by an intersection of:

the same row as the pixel of the selected column; and

a predetermined range of columns.

14. The system of claim 13, wherein the neighborhood has a range of at least two columns, wherein the infrared image data comprises 512 rows and 640 columns.

15. The system of claim 10, wherein the processor is adapted to execute instructions to perform the select, compare, adjust, and update operations for all remaining columns of the infrared image data.

16. The system of claim 10, wherein:

the infrared image data is first infrared image data;

the memory component is adapted to receive second infrared image data; and

the processor is adapted to execute instructions to;

apply the updated column correction term to the second infrared image data to provide second corrected infrared image data, and

perform the select, compare, adjust, and update operations using the second corrected infrared image data to further update the column correction term.

17. The system of claim 10, wherein the processor is adapted to execute instructions to:

apply the updated column correction term to the infrared image data to provide corrected infrared image data; and

repeat the compare, adjust, and update operations for the selected column using the corrected infrared image data.

18. The system of claim 10, wherein the first and second counters are first and second column-based processing counters, wherein the neighborhood pixels are first neighborhood pixels, wherein the processor is adapted to execute instructions to:

select one of the rows;

for each pixel of the selected row, compare the pixel to a corresponding plurality of second neighborhood pixels;

for each comparison, adjust a first row-based processing counter if the pixel of the selected row has a value greater than the compared second neighborhood pixel;

for each comparison, adjust a second row-based processing counter if the pixel of the selected row has a value less than the compared second neighborhood pixel; and

selectively update a row correction term associated with the selected row based on the first and second row-based processing counters.