Data processing method

• US 9,881,356 B2
• Filed: 11/21/2014
• Issued: 01/30/2018
• Est. Priority Date: 12/10/2013
• Status: Active Grant

• Current Assignee: BAE Systems Plc
• Original Assignee: BAE Systems Plc
• Inventors: Killey, Ainsley, Dale, Philip
• Primary Examiner(s): Bayat, Ali
• Application Number:
  US15/102,057
• Publication Number:
  US 20160314561A1
• Time in Patent Office: 1,166 Days
• CPC Class Codes: G06T 2207/10036 Multispectral image; Hyperspectral image
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/30181 Earth observation
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/92 based on global image properties

Abstract

A data processing method is disclosed for processing hyperspectral image data of a scene. The method comprises sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions and calculating a set of global statistical parameters and data correction factors using the data forming the data set. The method further comprises receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set, and subsequently calculating a set of local statistical parameters using the data of the further data portion. The method further comprises updating the set of global statistical parameters using the set of local statistical parameters and correcting the data of the data portion removed from the data set using the correction factors. The method further comprises outputting the corrected data portion and set of global statistical parameters calculated using the data set comprising the removed data portion, to a processor.

Claims

1. A data processing method for processing hyperspectral image data of a scene, the method comprising:

a) sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions;

b) calculating a set of global statistical parameters and data correction factors using the data forming the data set;

c) receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set,

d) calculating a set of local statistical parameters using the data of the further data portion;

e) updating the set of global statistical parameters using the set of local statistical parameters;

f) correcting the data of the data portion removed from the data set using the correction factors; and

g) outputting the corrected data portion and set of global statistical parameters calculated using the data set comprising the removed data portion, to a processor.

2. A data processing method according to claim 1, further comprising repeating steps (c) to (g).

3. A data processing method according to claim 2, further comprising recalculating the data correction factors when the data buffer receives the predefined number of further data portions.

4. A data processing method according to claim 2 further comprising sequentially receiving each set of local statistical parameters corresponding to each removed data portion, to a further data buffer, until a further predefined number of local sets have been received in the further data buffer to form a further data set.

5. A data processing method according to claim 4, further comprising receiving a further set of local statistical parameters at the further data buffer and removing the earliest received set of local statistical parameters from the further data set for each subsequent further data portion received at the data buffer.

6. A data processing method according to claim 1, wherein the global statistical parameters comprise a mean and a covariance of the data forming the data set, and the local statistical parameters comprise a mean and a covariance of the data forming the data portion.

7. A data processing method according to claim 1, further comprising processing the outputted corrected data portion and set of global statistical parameters according to a detection algorithm to locate targets within the scene.

15. A data processing method according to claim 1, further comprising:

a) imaging the scene to determine a scene object contrast factor; and

,

b) calculating the global set of statistical parameters, the set of local statistical parameters, and the data correction factors in dependence upon the scene object contrast factor.

16. Apparatus comprising a processor configured to execute the data processing method of claim 1.

8. A data processing method for processing hyperspectral image data of a scene, the method comprising:

a) sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions;

b) calculating a global set of statistical parameters and data correction factors using the data forming the data set;

c) receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set,

d) calculating a first set of local statistical parameters using the data of the further data portion;

e) calculating a second set of local statistical parameters using the data of the removed data portion;

f) updating the global set of statistical parameters using the first set of local statistical parameters;

g) outputting the second set of local statistical parameters to a further data buffer;

h) correcting the data of the data portion removed from the data set using the correction factors; and

i) outputting the corrected data portion and global set of statistical parameters calculated using the data set comprising the removed data portion, to a processor.

9. A data processing method according to claim 8, further comprising repeating steps (c) to (i).

10. A data processing method according to claim 9, further comprising sequentially receiving the sets of second local statistical parameters at the further data buffer, until the further data buffer comprises a further predefined number of sets of second local statistical parameters, to form a further data set.

11. A data processing method according to claim 10, further comprising receiving a further set of second local statistical parameters at the further data buffer and removing the earliest received set of second local statistical parameters from the further data set.

12. A data processing method according to claim 8, further comprising recalculating the data correction factors when the data buffer receives the predefined number of further data portions.

13. A data processing method according to claim 8, wherein the global set of statistical parameters comprise a mean and covariance of the data forming the data set, and the first and second sets of local statistical parameters comprise means and covariances of the data forming the further and removed data portions, respectively.

14. A data processing method according to claim 8, further comprising processing the outputted corrected data portion and set of global statistical parameters according to a detection algorithm to locate targets within the scene.

17. A data processing method according to claim 8, further comprising:

a) imaging the scene to determine a scene object contrast factor; and

,

b) calculating the global set of statistical parameters, the first and second sets of local statistical parameters, and the data correction factors in dependence upon the scene object contrast factor.

18. An apparatus comprising a processor configured to process hyperspectral image data of a scene by executing the following data processing steps:

a) sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions;

b) calculating a global set of statistical parameters and data correction factors using the data forming the data set;

c) receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set,

d) calculating a first set of local statistical parameters using the data of the further data portion;

e) calculating a second set of local statistical parameters using the data of the removed data portion;

f) updating the global set of statistical parameters using the first set of local statistical parameters;

g) outputting the second set of local statistical parameters to a further data buffer;

h) correcting the data of the data portion removed from the data set using the correction factors; and

i) outputting the corrected data portion and global set of statistical parameters calculated using the data set comprising the removed data portion, to a processor”

).