System and method for performing optical navigation using enhanced frames of image data

• US 8,189,954 B2
• Filed: 01/30/2009
• Issued: 05/29/2012
• Est. Priority Date: 01/30/2009
• Status: Active Grant

• Current Assignee: PixArt Imaging Incorporated
• Original Assignee: Avago Technologies ECBU IP Singapore Pte Limited (Broadcom, Inc.)
• Inventors: Brosnan, Michael J.
• Primary Examiner(s): Kassa, Yosef
• Application Number:
  US12/362,663
• Publication Number:
  US 20100195935A1
• Time in Patent Office: 1,215 Days
• Field of Search: 382/260, 382/274, 382/275
• US Class Current: 382/275
• CPC Class Codes: G06F 3/0317 in co-operation with a patterned surface, e.g. absolute position or relative movement detection for an optical mouse or pen positioned with respect to a coded surface

Abstract

A system and method for performing optical navigation uses a spatial noise pattern estimate of the spatial noise pattern in captured frames of image data caused by contamination on at least one component of the system to substantially remove the spatial noise pattern in the captured frames of image data before the captured frames of image data are used for displacement estimation.

Claims

1. A system for optical navigation comprising:

an image sensor configured to capture frames of image data of a target surface;

a spatial noise pattern estimation module configured to produce a spatial noise pattern estimate of a spatial noise pattern in the captured frames of image data caused by contamination on at least one component of the system using at least some of the captured frames of image data;

a normalization module configured to normalize particular frames of image data using the spatial noise pattern estimate to substantially remove the spatial noise pattern from the particular frames of image data to produce normalized frames of image data; and

a navigation engine configured to generate displacement values based on the normalized frames of image data.

2. The system of claim 1 wherein the spatial noise pattern estimation module is configured to average some of the captured frames of image data to produce the spatial noise pattern estimate.

3. The system of claim 2 wherein the spatial noise pattern estimation module is configured to average the first N number of the captured frames of image data after an initial movement is detected to produce the spatial noise pattern estimate, where N is an integer greater than one.

4. The system of claim 3 wherein the spatial noise pattern estimation module is configured to update the spatial noise pattern estimate using later captured frames of image data that were captured subsequent to the first N number of the captured frames of image data by weight averaging the later captured frames of image data and the spatial noise pattern estimate.

5. The system of claim 2 wherein the spatial noise pattern estimation module is configured to average the captured frames of image data which exhibit substantially different image brightness than prior captured frames of image data.

6. The system of claim 2 wherein the spatial noise pattern estimation module is configured to average the captured frames of image data obtained after substantial movement compared to prior captured frames of image data.

7. The system of claim 1 wherein the normalization module is configured to normalize the particular frames of image data using pixel values of the spatial noise pattern estimate as normalization factors for corresponding pixel values of the particular frames of image data.

8. The system of claim 1 further comprising:

an intensity estimation module configured to produce an intensity variation estimate of intensity variations in the captured frames of image data caused by at least one electrical component using some of the captured frames of image data; and

an intensity compensation module configured to compensate for the intensity variations in at least some of the captured frame of image data using the intensity variation estimate.

9. A method for performing optical navigation, the method comprising:

capturing frames of image data of a target surface;

producing a spatial noise pattern estimate of a spatial noise pattern in the captured frame of image data caused by contamination on at least one component used to capture the frames of image data;

normalizing particular frames of image data using the spatial noise pattern estimate to substantially remove the spatial noise pattern from the particular frames of image data to produce normalized frames of image data; and

generating displacement values based on the normalized frames of image data.

10. The method of claim 9 wherein the producing of the spatial noise pattern estimate includes averaging some of the captured frames of image data to produce the spatial noise pattern estimate.

11. The method of claim 10 wherein the averaging of some of the captured frames of image data includes averaging the first N number of the captured frames of image data after an initial movement is detected to produce the spatial noise pattern estimate, where N is an integer greater than one.

12. The method of claim 11 wherein the producing of the spatial noise pattern estimate includes updating the spatial noise pattern estimate using later captured frames of image data that were captured subsequent to the first N number of captured frames of image data by weight averaging the later captured frames of image data and the spatial noise pattern estimate.

13. The method of claim 9 wherein the normalizing of the particular frames of image data includes normalizing the particular frames of image data using pixel values of the spatial noise pattern estimate as normalization factors for corresponding pixel values of the particular frames of image data.

14. The method of claim 9 further comprising:

producing an intensity variation estimate of intensity variations in the captured frames of image data caused by at least one electrical component using some of the captured frames of image data; and

compensating the intensity variations in at least some of the captured frame of image data using the intensity variation estimate.

15. The method of claim 9 wherein the capturing of the frames of image data includes emitting light onto the target surface.

16. A method for performing optical navigation, the method comprising:

capturing frames of image data of a target surface, each of the captured frames of image data including a plurality of pixel values;

producing a spatial noise pattern estimate of a spatial noise pattern in the captured frame of image data caused by contamination on at least one component used to capture the frames of image data, wherein the producing of the spatial noise pattern estimate includes averaging the pixel values of some of the captured frames of image data;

normalizing particular frames of image data using the spatial noise pattern estimate to substantially remove the spatial noise pattern from the particular frames of image data to produce normalized frames of image data; and

generating displacement values based on the normalized frames of image data.

17. The method of claim 16 wherein the averaging of the pixel values of some of the captured frames of image data includes averaging the pixel values of the first N number of the captured frames of image data after an initial movement is detected to produce the spatial noise pattern estimate, where N is an integer greater than one.

18. The method of claim 17 wherein the producing of the spatial noise pattern estimate includes updating the spatial noise pattern estimate using later captured frames of image data that were captured subsequent to the first N number of captured frames of image data by weight averaging pixel values of the later captured frames of image data and values of the spatial noise pattern estimate.

19. The method of claim 16 wherein the normalizing of the particular frames of image data includes normalizing the particular frames of image data using pixel values of the spatial noise pattern estimate as normalization factors for corresponding pixel values of the particular frames of image data.

20. The method of claim 16 further comprising:

producing an intensity variation estimate of intensity variations in the captured frames of image data caused by at least one electrical component using some of the captured frames of image data; and

compensating the intensity variations in at least some of the captured frame of image data using the intensity variation estimate.