Method and system for adaptive pixel replacement

• US 9,355,435 B2
• Filed: 03/13/2014
• Issued: 05/31/2016
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: DRS Network & Imaging Systems, LLC (Leonardo S.p.A.)
• Original Assignee: DRS Network & Imaging Systems, LLC (Leonardo S.p.A.)
• Inventors: Neal, Henry W., Hutchison, David C., Blettner, Douglas A.
• Primary Examiner(s): Alavi, Amir
• Application Number:
  US14/208,901
• Publication Number:
  US 20140270562A1
• Time in Patent Office: 810 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20216 Image averaging
• CPC Class Codes: G06T 2207/20224 Image subtraction
• 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 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/254 involving subtraction of images

Abstract

A system and method of image processing is provided, including implementing adaptive pixel replacement techniques or reducing noise. The method includes obtaining a data map of an image frame, wherein the data map comprises good pixels and bad pixels at locations associated with the data map. The method also includes assigning different techniques to the bad pixels, wherein a first technique is assigned to a first bad pixel and a second technique is assigned to a second bad pixel. The method further includes adjusting information associated with the bad pixels for a chosen technique for each of the bad pixels.

Claims

1. A method of replacing a plurality of pixel values associated with an image frame, the method comprising:

obtaining a data map of the image frame, wherein the data map comprises good pixels at a first set of locations associated with the data map and bad pixels at a second set of locations associated with the data map, and wherein the bad pixels includes a first bad pixel and a second bad pixel;

identifying one or more pixel replacement techniques to generate the adaptive pixel replacement mask, wherein the one or more pixel replacement techniques includes a first pixel replacement technique and a second pixel replacement technique;

assigning the first pixel replacement technique to the first bad pixel in the adaptive pixel replacement mask;

assigning the second pixel replacement technique to the second bad pixel in the adaptive pixel replacement mask, wherein the second pixel replacement technique is different from the first pixel replacement technique;

adjusting a first pixel value associated with the first bad pixel using the first pixel replacement technique; and

adjusting a second pixel value associated with the second bad pixel using the second pixel replacement technique.

2. The method of claim 1 wherein the first pixel replacement technique and the second bad pixel replacement technique comprise at least one of left good pixel, right good pixel, local average, spiral search, upper replacement, or lower replacement.

3. The method of claim 1 wherein the first technique is a local average technique and the second technique is a spiral search technique.

4. The method of claim 1 further comprising:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel and the second pixel in a single row, and the first pixel and a third pixel in a single column; and

when the first pixel, the second pixel, and the third pixel are bad pixels, assigning spiral search as the first pixel replacement technique for the first pixel.

5. The method of claim 1 further comprising:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel and the second pixel in a single row, and the first pixel and a third pixel in a single column; and

when the first pixel and the second pixel are bad pixels and the third pixel is a good pixel, assigning local average as the first pixel replacement technique for the first pixel.

6. The method of claim 1 further comprising:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel, the second pixel, a third pixel, and a fourth pixel, wherein the second pixel, the third pixel, and the fourth pixel are directly next to the first pixel; and

when the second pixel, the third pixel, and the fourth pixel are bad pixels, assigning spiral search as the first pixel replacement technique for the first pixel.

7. The method of claim 1 further comprising:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel, the second pixel, a third pixel, and a fourth pixel, wherein the first pixel, the second pixel, the third pixel, and the fourth pixel are horizontally aligned in a row on the data map, and wherein the first pixel is to the left of the second pixel, the second pixel is to the left of the third pixel, and the third pixel is to the left of the fourth pixel; and

when the first pixel is a good pixel and the second pixel, the third pixel, and the fourth pixel are bad pixels, and when the plurality of pixels of the data map that are above and below the second pixel are bad pixels, assigning left good pixel as the second pixel replacement technique for the second pixel.

8. The method of claim 1 further comprising:

updating the data map in real time.

9. The method of claim 1 wherein assigning the first pixel replacement technique to the first bad pixel and assigning the second pixel replacement technique to the second bad pixel is conducted during a calibration process.

10. A system for replacing a plurality of pixel values associated with an image frame, the system comprising:

a processor; and

a computer readable medium coupled to the processor, the computer readable medium comprising instructions that cause the processor to implement a method comprising;

obtaining a data map of the image frame, wherein the data map comprises good pixels at a first set of locations associated with the data map and bad pixels at a second set of locations associated with the data map, and wherein the bad pixels includes a first bad pixel and a second bad pixel;

identifying one or more pixel replacement techniques to generate the adaptive pixel replacement mask, wherein the one or more pixel replacement techniques includes a first pixel replacement technique and a second pixel replacement technique;

assigning the first pixel replacement technique to the first bad pixel in the adaptive pixel replacement mask;

assigning the second pixel replacement technique to the second bad pixel in the adaptive pixel replacement mask, wherein the second pixel replacement technique is different from the first pixel replacement technique;

adjusting a first pixel value associated with the first bad pixel using the first pixel replacement technique; and

adjusting a second pixel value associated with the second bad pixel using the second pixel replacement technique.

11. The system of claim 10 wherein the first pixel replacement technique and the second bad pixel replacement technique comprise at least one of left good pixel, right good pixel, local average, spiral search, upper replacement, or lower replacement.

12. The system of claim 10 wherein the first technique is a local average technique and the second technique is a spiral search technique.

13. The system of claim 10 wherein the method further comprises:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel and the second pixel in a single row, and the first pixel and a third pixel in a single column; and

when the first pixel, the second pixel, and the third pixel are bad pixels, assigning spiral search as the first pixel replacement technique for the first pixel.

14. The system of claim 10 wherein the method further comprises:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel and the second pixel in a single row, and the first pixel and a third pixel in a single column; and

when the first pixel and the second pixel are bad pixels and the third pixel is a good pixel, assigning local average as the first pixel replacement technique for the first pixel.

15. The system of claim 10 wherein the method further comprises:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel, the second pixel, a third pixel, and a fourth pixel, wherein the second pixel, the third pixel, and the fourth pixel are directly next to the first pixel; and

when the second pixel, the third pixel, and the fourth pixel are bad pixels, assigning spiral search as the first pixel replacement technique for the first pixel.

16. The system of claim 10 wherein the method further comprises:

analyzing a plurality of pixels of the data map, wherein the plurality of pixels includes the first pixel, the second pixel, a third pixel, and a fourth pixel, wherein the first pixel, the second pixel, the third pixel, and the fourth pixel are horizontally aligned in a row on the data map, and wherein the first pixel is to the left of the second pixel, the second pixel is to the left of the third pixel, and the third pixel is to the left of the fourth pixel; and

when the first pixel is a good pixel and the second pixel, the third pixel, and the fourth pixel are bad pixels, and when the plurality of pixels of the data map that are above and below the second pixel are bad pixels, assigning left good pixel as the second pixel replacement technique for the second pixel.

17. The system of claim 10 wherein the method further comprises:

updating the data map in real time.

18. The system of claim 10 wherein the method further comprises:

replacement technique to the first bad pixel and assigning the second pixel replacement technique to the second bad pixel is conducted during a calibration process.

19. A non-transitory computer readable medium storing a plurality of instructions that when executed control a computer system to replace a plurality of pixel values associated with an image frame, the instructions comprising:

obtain a data map of the image frame, wherein the data map comprises good pixels at a first set of locations associated with the data map and bad pixels at a second set of locations associated with the data map, and wherein the bad pixels includes a first bad pixel and a second bad pixel;

identify one or more pixel replacement techniques to generate the adaptive pixel replacement mask, wherein the one or more pixel replacement techniques includes a first pixel replacement technique and a second pixel replacement technique;

assign the first pixel replacement technique to the first bad pixel in the adaptive pixel replacement mask;

assign the second pixel replacement technique to the second bad pixel in the adaptive pixel replacement mask, wherein the second pixel replacement technique is different from the first pixel replacement technique;

adjust a first pixel value associated with the first bad pixel using the first pixel replacement technique; and

adjust a second pixel value associated with the second bad pixel using the second pixel replacement technique.

20. The computer readable medium of claim 19 wherein the first pixel replacement technique and the second bad pixel replacement technique comprise at least one of left good pixel, right good pixel, local average, spiral search, upper replacement, or lower replacement.