Methods and apparatus for detecting defects in imaging arrays by image analysis
AssigneeSimon Fraser University
InventorsGlenn Harrison Chapman, Israel Koren, Zahava Koren, Jozsef Dudas, Cory Jung
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Abstract
Methods for detecting defective pixels in imaging arrays involve establishing probabilities that individual pixels are defective and updating those probabilities by analysing images acquired by the imaging arrays. Probabilities may be evaluated for each of two or more defect conditions. The methods may be used to detect defects such as stuck-low, stuck-high, high-sensitivity, low sensitivity, hot, and defect-free conditions. Other more complicated defect conditions can also be detected. Apparatus for detecting defective pixels may be integrated with a camera or other imaging device or provided separately.
Claims60
A method for detecting defects in imaging arrays comprising arrays of pixels, the method comprising,
- obtaining a set of images acquired by an imaging array, each image comprising a set of pixel values corresponding to pixels of the image;
- taking each of a plurality of images in the set as a current image and obtaining for at least one of the pixels, for each of one or more of a plurality of defect types, a corresponding updated probability, the updated probability based at least in part upon:
- a pixel value corresponding to the at least one pixel;
- statistics of pixel values of other pixels in the current image;
- and
- one or more prior probabilities that the one of the pixels has the corresponding defect type.
A method for categorizing a pixel of an imaging array into one of a plurality of defect types, the method comprising:
- acquiring an image taken by the imaging array;
- obtaining an image statistic for the image;
- and,
- determining a probability that the pixel has one of the defect types based at least in part upon a pixel value corresponding to the pixel in the image and the image statistic;
- wherein the image is one of a plurality of images acquired by the imaging array and the method comprises repeating the steps of acquiring an image, obtaining an image statistic for the image and determining a probability that the pixel has one of the defect types for each of the plurality of images and determining an updated probability that the pixel has the one of the defect types based upon the probability determined for each of the plurality of images.
A method for detecting defects in imaging arrays comprising an array of pixels, the method comprising:
- acquiring a set of images taken by the imaging array during normal operation;
- for each of the images, acquiring a statistical distribution of the pixel output values in the image;
- for each of a plurality of pixels, evaluating a probability that the pixel has a defect condition based at least in part on the pixel value and the statistical distribution;
- establishing a plurality of pixel defect types to be identified and for each of the pixels, for each of the defect types, evaluating a probability that the pixel has the defect type;
- and,
- prior to evaluating the probability that the pixel has a defect condition:
- specifying a model behavior for each defect type;
- and
- for each defect type, establishing an initial probability for each pixel that the pixel has the defect type.
A method for determining sensitivities of elements in an imaging array comprising an array of imaging elements, the method comprising:
- providing a plurality of sensitivity models, each corresponding to a different sensitivity;
- acquiring a set of images taken by the imaging array, each image comprising an array of pixels;
- for each of the images, acquiring a statistical distribution of pixel values in the image;
- for each of the images creating a predicted statistical distribution for each of the sensitivity models based at least in part upon the statistical distribution and the sensitivity models;
- and,
- for each of the images obtaining a conditional probability that a pixel matches each of the sensitivity models based at least in part on the pixel value of the pixel and the predicted statistical distribution corresponding to the sensitivity model.
Dependencies are inferred from the claim text.