Fixed Pattern Noise Reduction

• US 20140078348A1
• Filed: 09/20/2012
• Published: 03/20/2014
• Est. Priority Date: 09/20/2012
• Status: Active Grant

• Current Assignee: Gyrus ACMI, Inc. (Olympus Corporation)
• Original Assignee: Gyrus ACMI, Inc. (Olympus Corporation)
• Inventors: Skarbnik, Nikolay, Wolf, Stuart, Zilberstein, Chaya, Starodubsky, Natalie
• Granted Patent: US 9,854,138 B2
• Time in Patent Office: Days
• US Class Current: 348/241
• CPC Class Codes: H04N 25/63 applied to dark current
• CPC Class Codes: H04N 25/67 applied to fixed-pattern noise, e.g. non-uniformity of response
• CPC Class Codes: H04N 25/671 for non-uniformity detection or correction
• CPC Class Codes: H04N 25/672 between adjacent sensors or output registers for reading a single image

Abstract

A method, including receiving signals, from a rectangular array of sensor elements arranged in rows and columns, corresponding to an image captured by the array. The method also includes analyzing the signals along a row or a column to identify one or more local turning points, and processing the signals at the identified local turning points to recognize fixed pattern noise in the captured image. The method further includes correcting values of the signals from the sensor elements at the identified local turning points so as to reduce the fixed pattern noise in the image.

Claims

1. A method, comprising:

receiving signals, from a rectangular array of sensor elements arranged in rows and columns, corresponding to an image captured by the array;

analyzing the signals along a row or a column to identify one or more local turning points;

processing the signals at the identified local turning points to recognize fixed pattern noise in the captured image; and

correcting values of the signals from the sensor elements at the identified local turning points so as to reduce the fixed pattern noise in the image.

2. The method according to claim 1, wherein the one or more local turning points comprise one or more local minima.

3. The method according to claim 2, wherein processing the signals to recognize the fixed pattern noise comprises determining that an absolute value of differences of the signals at the one or more local minima is less than a predetermined threshold.

4. The method according to claim 3, wherein the predetermined threshold is a function of a noise level of the sensor elements, and wherein correcting the values of the signals comprises adding the noise level to the signals at the one or more local minima.

5. The method according to claim 1, wherein the one or more local turning points comprise one or more local maxima.

6. The method according to claim 5, wherein processing the signals to recognize the fixed pattern noise comprises determining that an absolute value of differences of the signals at the one or more local maxima is less than a predetermined threshold.

7. The method according to claim 6, wherein the predetermined threshold is a function of a noise level of the sensor elements, and wherein correcting the values of the signals comprises subtracting the noise level from the signals at the one or more local maxima.

8. The method according to claim 1, wherein analyzing the signals along the row or the column comprises evaluating the signals of a given sensor element and of nearest neighbor sensor elements of the given sensor element along the row or the column.

9. The method according to claim 8, wherein the nearest neighbor sensor elements comprise a first sensor element and a second sensor element, and wherein the first sensor element, the given sensor element, and the second sensor element are contiguous.

10. The method according to claim 8, wherein the nearest neighbor sensor elements comprise a first plurality of sensor elements and a second plurality of sensor elements, wherein the first and the second pluralities are disjoint, and wherein the given sensor element lies between the first and the second pluralities.

11. The method according to claim 1, wherein the sensor elements along the row or the column comprise first elements configured to detect a first color and second elements configured to detect a second color different from the first color, and wherein analyzing the signals along the row or the column comprises analyzing the signals from the first elements to identify the one or more local turning points.

12. A method, comprising:

receiving signals, from a rectangular array of sensor elements arranged in rows and columns, corresponding to an image captured by the array;

identifying a first row and a second row contiguous with the first row; and

prior to receiving second row signals from the second row;

receiving first row signals from the first row;

analyzing the first row signals along the first row to identify one or more first row local turning points;

processing the first row signals at the identified first row local turning points to recognize fixed pattern noise in the captured image; and

correcting values of the first row signals from the sensor elements at the identified first row local turning points so as to reduce the fixed pattern noise in the image.

13. The method according to claim 12, wherein the one or more first row local turning points comprise one or more first row local minima.

14. The method according to claim 12, wherein the one or more first row local turning points comprise one or more first row local maxima.

15. A method, comprising:

receiving signals, from a rectangular array of sensor elements arranged in rows and columns, corresponding to an image captured by the array;

analyzing the signals along a diagonal of the array to identify one or more local turning points;

processing the signals at the identified local turning points to recognize fixed pattern noise in the captured image; and

correcting values of the signals from the sensor elements at the identified local turning points so as to reduce the fixed pattern noise in the image.

16. Apparatus, comprising:

a rectangular array of sensor elements arranged in rows and columns, configured to output signals corresponding to an image captured by the array; and

a processor which is configured to;

analyze the signals along a row or a column to identify one or more local turning points,

process the signals at the identified local turning points to recognize fixed pattern noise in the captured image, and

correct values of the signals from the sensor elements at the identified local turning points so as to reduce the fixed pattern noise in the image.

17. Apparatus, comprising:

a rectangular array of sensor elements arranged in rows and columns, configured to output signals corresponding to an image captured by the array; and

a processor which is configured to;

identify a first row and a second row contiguous with the first row, and

prior to receiving second row signals from the second row;

receive first row signals from the first row,

analyze the first row signals along the first row to identify one or more first row local turning points,

process the first row signals at the identified first row local turning points to recognize fixed pattern noise in the captured image, and

correct values of the first row signals from the sensor elements at the identified first row local turning points so as to reduce the fixed pattern noise in the image.

18. Apparatus, comprising:

a rectangular array of sensor elements arranged in rows and columns, configured to output signals corresponding to an image captured by the array; and

a processor which is configured to;

analyze the signals along a diagonal of the array to identify one or more local turning points,

process the signals at the identified local turning points to recognize fixed pattern noise in the captured image, and

correct values of the signals from the sensor elements at the identified local turning points so as to reduce the fixed pattern noise in the image.