Method and Apparatus for Improving Photo Image Quality

• US 20090174782A1
• Filed: 01/07/2008
• Published: 07/09/2009
• Est. Priority Date: 01/07/2008
• Status: Active Grant

• Current Assignee: DP Technologies, Inc.
• Original Assignee: Fullpower Technologies Incorporated
• Inventors: Kinsolving, Arthur, Kahn, Philippe, Easwar, Venkat
• Granted Patent: US 8,040,382 B2
• Time in Patent Office: Days
• US Class Current: 348/208.200
• CPC Class Codes: G02B 27/646 compensating for small deviations, e.g. due to vibration or shake movement of one or more optical elements for control of motion blur in cameras, projectors or printers G03B2205/0007; image stabilisation in cameras peculiar to the presence or use of an electronic image sensor H04N23/68
• CPC Class Codes: H04N 23/68 for stable pick-up of the scene, e.g. compensating for camera body vibrations
• CPC Class Codes: H04N 23/6812 based on additional sensors, e.g. acceleration sensors
• CPC Class Codes: H04N 5/145 Movement estimation for video coding H04N19/51

Abstract

A method and apparatus for receiving motion data and determining acceleration vectors based on biomechanical data and the received motion data. The method further comprises creating an improved image based on the acceleration vectors.

Claims

1. A method comprising:

receiving motion data of an image capture device;

determining sinusoids that describe the motion of the image capture device, based on biomechanical data and the received motion data;

creating an improved image based on the sinusoids.

2. The method of claim 1, wherein the sinusoids are derived from acceleration vectors.

3. The method of claim 1, wherein the sinusoids are derived from one or more of the following:

velocity vectors, angular velocity vectors, acceleration vectors.

4. The method of claim 1, wherein creating the improved image comprises selecting a point of minimum adverse motion to take the image, based on the biomechanical data and the received motion data.

5. The method of claim 4, further comprising:

predicting an acceleration waveform based on acceleration vectors;

estimating motion based on the acceleration waveform and the biomechanical data; and

identifying points of minimum motion based on the motion estimation.

6. The method of claim 5, further comprising:

overlaying the point of minimum motion with a frame sync signal; and

activating an image capture mechanism at a frame sync point that is close to the point of minimum motion.

7. The method of claim 5, further comprising:

utilizing spectral estimation to predict the acceleration wave form.

8. The method of claim 7, further comprising:

utilizing a bandpass filter, and a narrow band filter to isolate a frequency; and

detecting phases and amplitudes of the frequencies, the phases and amplitudes utilized for the prediction of the acceleration waveform.

9. The method of claim 5, further comprising:

utilizing a quadrature filter to calculate a phase shifted signal;

calculating phase based on the phase shifted signal and the original signal; and

predicting the waveform based on an amplitude and the phase.

10. The method of claim 1, wherein creating the improved image comprises removing blur from an image in post processing on the basis of the biomechanical data and the received motion data.

11. The method of claim 10, further comprising:

calculating a global motion vector based on the motion data; and

adjusting a captured image based on the global motion vector.

12. The method of claim 11, wherein the global motion vector is a constant for a sub-portion of the captured image, and the adjusting is for the sub-portion.

13. The method of claim 1, further comprising, in a video:

identifying a frame having minimal global motion;

designating the frame as an I frame for encoding purposes.

14. The method of claim 13, further comprising:

identifying a blurry frame based on projected motion calculated from the acceleration vectors and the biomechanical information;

removing the blurry frame; and

replacing the blurry frame with a frame interpolated from adjacent frames.

15. The method of claim 1, further comprising:

receiving data from a cardiac sensor; and

utilizing the data from the cardiac sensor to predict the sinusoids.

16. The method of claim 1, further comprising:

a proximity sensor input to initiate prediction and capture process prior to actual shutter press.

17. An image improvement system for an image capture device, the system comprising:

a receiving logic to receive motion data of the image capture device;

a sinusoidal signal analysis logic to calculate sinusoids that describe the motion of the image capture device, based on biomechanical data and the received motion data;

the image improvement system to create an improved image based on the sinusoids.

18. The system of claim 17, wherein the sinusoids are derived from one or more of the following:

velocity vectors, angular velocity vectors, acceleration vectors.

19. The system of claim 17, further comprising:

a pre-processing system to select a point of minimum adverse motion to take the image, based on the biomechanical data and the received motion data.

20. The system of claim 19, further comprising:

a minimum motion identification logic to estimate motion based on the sinusoids and to identify points of minimum motion; and

an overlay logic to overlay the points of minimum motion with a frame sync signal; and

a shutter logic to activate an image capture mechanism at a frame sync point that is close to the point of minimum motion.

21. The system of claim 20, further comprising:

a proximity sensor input to initiate prediction and capture process prior to actual shutter press.

22. The system of claim 19, further comprising:

a bandpass filter to isolate a frequency;

a spectral estimator to predict the acceleration wave form; and

a phrase detector and an amplitude detector to identify phases and amplitudes of the frequency, the phases and amplitudes utilized for the prediction of the acceleration waveform.

23. The system of claim 19, further comprising:

a quadrature filter to calculate a phase shifted signal;

an Arc Tan calculator to calculate phase based on the phase shifted signal and the original signal; and

prediction waveform generator to predict the waveform based on an amplitude and the phase.

24. The system of claim 17, further comprising a post-processing system to create the improved image by removing blur from an image on the basis of the biomechanical data and the received motion data.

25. The system of claim 24, further comprising:

a global motion vector calculator to calculate global motion vectors based on the motion data; and

image restoration logic to adjust a captured image based on the global motion vector.

26. The system of claim 25, wherein the global motion vector is a constant for a sub-portion of the captured image, and the adjusting is for the sub-portion of the captured image.

27. The system of claim 25, further comprising, in a video:

the global motion vector calculator to identify a frame having minimal global motion; and

the image restoration logic to designate the frame as an I frame for encoding purposes.

28. The system of claim 25, further comprising:

the image restoration logic to identify a blurry frame, remove the blurry frame, and replace the blurry frame with a frame interpolated from adjacent frames.

29. The system of claim 17, further comprising:

a cardiac sensor; and

a minimum motion identification logic utilizing data from the cardiac sensor to predict the sinusoids.