Combined Intensity And Coherent Change Detection In Images

• US 20170061217A1
• Filed: 06/20/2016
• Published: 03/02/2017
• Est. Priority Date: 08/31/2015
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Cha, Miriam, Phillips, Rhonda D., Wolfe, Patrick J., Richmond, Christ D.
• Granted Patent: US 10,037,477 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 18/2415 based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
• CPC Class Codes: G06V 10/758 Involving statistics of pixels or of feature values, e.g. histogram matching
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 2201/031 of internal organs
• CPC Class Codes: G06V 2201/07 Target detection

Abstract

Described embodiments detect changes in a scene over time using first and second images of the scene. A non-coherent intensity change detector detects large-scale changes between the first image and the second image and generates a large-scale change value for pairs of corresponding pixel locations in the first and second images. If the large-scale change value for a given pair of pixel locations reaches a threshold, a coherent change detector is used to detect small-scale changes between the first and second images. A small-scale change value is generated for the given pairs of pixel locations in the images. A composite change value is generated by combining the large-scale change value and the small-scale change value for each pixel pair. The change thresholds are used to determine whether a change in the scene has occurred over the time period.

Claims

1. A method of detecting changes in a scene over a time period, the method comprising:

using an imaging system to obtain a first image of the scene at a first time and a second image of the scene at a second, different time;

using a non-coherent intensity change detector to detect large-scale changes between the first image and the second image;

generating a large-scale change value for pairs of corresponding pixel locations in the first and second images;

in response to the large-scale change value for each pair of corresponding pixel locations reaching a selected large-scale change threshold, using a coherent change detector to detect small-scale changes between the first image and the second image;

generating a small-scale change value for selected ones of the pairs of corresponding pixel locations in the first and second images; and

generating a composite change value by combining the large-scale change value and the small-scale change value for each pixel pair, wherein the combining comprises;

determining (i) the large-scale change threshold, (ii) a small-scale change threshold, and (iii) a composite change threshold;

combining, based on the determined large-scale change threshold and the determined small-scale change threshold, the large-scale change value and the small-scale change value for each pixel pair; and

determining, based on the determined composite change threshold, whether a change in the scene has occurred over the time period.

2. The method of claim 1, wherein determining the large-scale change threshold, the small-scale change threshold, and the composite change threshold comprises:

determining a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of;

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image.

3. The method of claim 2, wherein determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold comprises at least one of:

heuristically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

theoretically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.

4. The method of claim 2, wherein determining a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of:

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image comprises determining the relationship given by;

5. The method of claim 1, wherein the imaging system comprises a Synthetic Aperture Radar (SAR).

6. The method of claim 1, wherein the imaging system comprises a Magnetic Resonance Imaging (MRI) system.

7. The method of claim 1, wherein a large-scale change corresponds to a large difference in pixel magnitude between the second image and the first image.

8. The method of claim 1, wherein a small-scale change corresponds to a difference in phase between pixels of the second image and the first image.

9. The method of claim 1, further comprising:

in response to the composite change value for each pair of corresponding pixel locations reaching the composite change threshold, generating an indication that at least one change was detected between the first and second images; and

providing the first and second images for further processing.

10. The method of claim 2, wherein determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold comprises at least one of:

empirically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

analytically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.

11. A change detection system for detecting changes in a scene over a time period, the change detection system comprising:

a processor configured to receive a first image of the scene at a first time and a second image of the scene at a second, different time;

a non-coherent intensity change detector configured to (i) detect large-scale changes between the first image and the second image, and (ii) generate a large-scale change value for pairs of corresponding pixel locations in the first and second images; and

a coherent change detector configured to (i) detect small-scale changes between the first image and the second image in response to the large-scale change value for each pair of corresponding pixel locations reaching a selected large-scale change threshold, and (ii) generate a small-scale change value for selected ones of the pairs of corresponding pixel locations in the first and second images;

the processor configured to generate a composite change value by combining the large-scale change value and the small-scale change value for each pixel pair, wherein to perform the combining the processor is configured to;

determine (i) the large-scale change threshold, (ii) a small-scale change threshold, and (iii) a composite change threshold;

combine, based on the determined large-scale change threshold and the heuristically determined small-scale change threshold, the large-scale change value and the small-scale change value for each pixel pair; and

determine, based on the determined composite change threshold, whether a change in the scene has occurred over the time period.

12. The change detection system of claim 11, wherein the first image and the second image generated by an image capture system coupled to the change detection system.

13. The change detection system of claim 12, wherein, to determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold, the processor is further configured to at least one of:

heuristically determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

theoretically determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.

14. The change detection system of claim 12, wherein the image capture system comprises a Synthetic Aperture Radar (SAR).

15. The change detection system of claim 12, wherein the image capture system comprises a Magnetic Resonance Imaging (MRI) system.

16. The change detection system of claim 11, wherein to heuristically determine the large-scale change threshold, the small-scale change threshold, and the composite change threshold, the processor is further configured to:

determine a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of;

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image.

17. The change detection system of claim 16, wherein to determine a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of:

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image, the processor is further configured to determine the relationship given by;

18. The change detection system of claim 11, wherein a large-scale change corresponds to a large difference in pixel magnitude between the second image and the first image.

19. The change detection system of claim 11, wherein a small-scale change corresponds to a difference in phase between pixels of the second image and the first image.

20. The change detection system of claim 11, wherein the processor is further configured to:

in response to the composite change value for each pair of corresponding pixel locations reaching the composite change threshold, generate an indication that at least one change was detected between the first and second images; and

provide the first and second images for further processing.

21. The change detection system of claim 12, wherein, to determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold, the processor is further configured to at least one of:

empirically determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

analytically determine (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.

22. A non-transitory machine-readable storage medium, having encoded thereon program code, wherein, when the program code is executed by a machine, the machine implements a method of detecting changes in a scene over a time period, the method comprising:

using an imaging system to obtain a first image of the scene at a first time and a second image of the scene at a second, different time;

using a non-coherent intensity change detector to detect large-scale changes between the first image and the second image;

generating a large-scale change value for pairs of corresponding pixel locations in the first and second images;

in response to the large-scale change value for each pair of corresponding pixel locations reaching a selected large-scale change threshold, using a coherent change detector to detect small-scale changes between the first image and the second image;

generating a small-scale change value for selected ones of the pairs of corresponding pixel locations in the first and second images; and

generating a composite change value by combining the large-scale change value and the small-scale change value for each pixel pair, wherein the combining comprises;

determining (i) the large-scale change threshold, (ii) a small-scale change threshold, and (iii) a composite change threshold;

combining, based on the determined large-scale change threshold and the heuristically determined small-scale change threshold, the large-scale change value and the small-scale change value for each pixel pair; and

determining, based on the determined composite change threshold, whether a change in the scene has occurred over the time period.

23. The non-transitory machine-readable storage medium of claim 22, wherein the imaging system comprises at least one of:

a Synthetic Aperture Radar (SAR) and a Magnetic Resonance Imaging (MRI) system.

24. The non-transitory machine-readable storage medium of claim 22, wherein determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold comprises at least one of:

heuristically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

theoretically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.

25. The non-transitory machine-readable storage medium of claim 22, wherein determining the large-scale change threshold, the small-scale change threshold, and the composite change threshold comprises:

determining a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of;

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image.

26. The non-transitory machine-readable storage medium of claim 25, wherein determining a relative likelihood for the large-scale change threshold and the small-scale change threshold by assigning pseudo-random positive values for at least one of:

a number of samples present in each image, a true change value, a variation value of the first image, and a variation value of the second image comprises determining the relationship given by;

27. The non-transitory machine-readable storage medium of claim 22, wherein a large-scale change corresponds to a large difference in pixel magnitude between the second image and the first image, and wherein a small-scale change corresponds to a difference in phase between pixels of the second image and the first image.

28. The non-transitory machine-readable storage medium of claim 22, further comprising:

in response to the composite change value for each pair of corresponding pixel locations reaching the composite change threshold, generating an indication that at least one change was detected between the first and second images; and

providing the first and second images for further processing.

29. The non-transitory machine-readable storage medium of claim 22, further comprising:

using the imaging system to obtain a plurality of images of the scene, each image obtained at different times; and

using the non-coherent intensity change detector and the coherent change detector to detect changes between one or more sets of the plurality of images of the scene.

30. The non-transitory machine-readable storage medium of claim 22, wherein determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold comprises at least one of:

empirically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold; and

analytically determining (i) the large-scale change threshold, (ii) the small-scale change threshold, and (iii) the composite change threshold.