Robust sequential approach in detecting defective pixels within an image sensor

• US 6,625,318 B1
• Filed: 11/13/1998
• Issued: 09/23/2003
• Est. Priority Date: 11/13/1998
• Status: Expired due to Fees

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Tan, Yap-Peng, Acharya, Tinku
• Primary Examiner(s): Patel, Jayanti K.
• Assistant Examiner(s): AZARIAN, SEYED H
• Application Number:
  US09/191,310
• Time in Patent Office: 1,775 Days
• Field of Search: 382/124, 382/127, 382/141, 382/224, 382/226, 382/229, 382/221, 382/220, 382/173, 382/275, 382/181, 356/124, 348/131
• US Class Current: 382/224
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: H04N 25/68 applied to defects

Abstract

What is disclosed is a method comprising performing an observation on a sensor having a plurality of pixels, for each of the pixels that are unclassified, determining a score according to the observation, if the score for the each pixel satisfies a stopping condition, classifying the each pixel as being one of either defective or functional, and repeating the steps of performing, determining and classifying for any the pixels remaining unclassified after determining the score.

Claims

1. A method of detecting defective sensors in a sensor array comprising:

performing an observation of an object on a sensor array having a plurality of pixels, each pixel corresponding to a sensor of said sensor array and each sensor generating a pixel value for the corresponding pixel;

for each of said pixels, determining a score based on statistical analysis of said pixel values using said observation; and

if said score for said each pixel satisfies a stopping condition, classifying said each pixel as being one of either defective or functional.

2. A method according to claim 1 wherein determining a score includes:

measuring image content; and

compiling statistics of said image content.

3. A method according to claim 2 wherein said image content includes pixel values.

4. A method according to claim 3 wherein said statistics include one or more of mean, variance and standard deviation measurements as a function of image content measured by the pixel values.

5. A method according to claim 1 wherein determining a score includes:

computing an individual likelihood ratio for each said observation; and

accumulating said individual likelihood ratios into said score.

6. A method according to claim 5 wherein said individual likelihood ratio is formed by a ratio of the probability that said each pixel is functional to the probability that said each pixel is defective.

7. A method according to claim 6 wherein said individual likelihood ratios are weighted in accordance with the relevance of said observation.

8. A method according to claim 7 wherein said relevance is a function of neighboring pixel intensity.

9. A method according to claim 6 wherein said probabilities are determined by measuring at minimum neighboring distance from said each pixel.

10. A method according to claim 9 wherein said minimum neighboring distance is determined by:

by computing absolute value of the pixel value differences between said each pixel and each of the neighboring pixels; and

finding a minimum among said absolute value of pixel value differences.

11. An article comprising a machine-readable medium having instructions stored thereon which when executed causes:

determining a score for each of a plurality of pixels, said pixels corresponding to an observation of an obect by sensors of a sensor array said score being based on statistical analysis of pixel values generated by said sensors according to said observation; and

if said score for said each pixel satisfies a stopping condition, classifying said each pixel as being one of either defective or functional.

19. An article according to claim 11, wherein determining a score comprises, compiling statistics of pixel values, wherein said statistics include one or more of mean, variance and standard deviation measurements as a function of image content measured by the pixel values.

20. An article according to claim 19, wherein determining a score includes:

computing an individual likelihood ratio for each said pixel for said observation;

accumulating said individual likelihood ratios into said score wherein said individual likelihood ratio is formed by a ratio of the probability that said each pixel is functional to the probability that said each pixel is defective wherein said individual likelihood ratios are weighted in accordance with neighboring pixel values.

12. A system comprising:

a memory capable of storing instructions and data related to defective pixel detection;

a processor coupled to said memory, said processor adapted to execute said instructions and manipulate said data to determine which pixels of an image sensor are defective, said instructions including;

for each of said pixels that are unclassified, determining a score based on statistical analysis of pixel values generated by said image sensor according to an observation; and

if said score for said each pixel satisfies a stopping condition, classifying said each pixel as being one of either defective or functional.

13. A system according to claim 12 further comprising:

an image sensor array providing data in the form of pixel values, each pixel corresponding to a sensor of said sensor array, said sensor array adapted to scan an image for each desired observation.

14. A system according to claim 12, comprising:

a defective pixel location memory adapted to store locations of pixels determined defective.

15. A system according to claim 13, wherein said image sensor scans are adjusted according to said pixels classified as defective.

16. A system according to claim 12, wherein determining a score comprises, compiling statistics of pixel values, wherein said statistics include one or more of mean, variance and standard deviation measurements as a function of image content measured by the pixel values.

17. A system according to claim 12, wherein determining a score includes:

computing an individual likelihood ratio for each said pixel for said observation;

accumulating said individual likelihood ratios into said score wherein said individual likelihood ratio is formed by a ratio of the probability that said each pixel is functional to the probability that said each pixel is defective wherein said individual likelihood ratios are weighted in accordance with neighboring pixel values.

18. A system according to claim 17, wherein said probabilities are determined by measuring at minimum neighboring distance from said each pixel wherein said minimum neighboring distance is determined by computing absolute values of the pixel value differences between said each pixel and each of said neighboring pixels and finding a minimum among said absolute values of pixel value differences.