Image correcting method
AssigneeAdvanced Mask Inspection Technology Inc.
InventorJunji Oaki
Life of this patent
Estimating the term…
Abstract
In a reticle inspecting apparatus or the like, there is provided an image correcting method which is effective when a rank of a matrix lacks due to continuous equal grayscale values when an image is handled as a matrix. In the image correcting method, a random noise image having fine grayscale is superposed on a pattern image to make a matrix full-rank.
Claims8
An image correcting method for generating a correction image from two types of pattern images, said method comprising:
- generating a random noise pattern image at least in regions having almost equal grayscale values in the pattern image;
- superposing the random noise pattern image at least on the regions having the almost equal grayscale values, and wherein
- the random noise pattern image has grayscale values which are finer than the grayscale values of the pattern image.
An image correcting method for generating a correction image from an inspection reference pattern image and a pattern image under test, said method comprising:
- generating a random noise pattern image having grayscale values which are finer than the grayscale values of the inspection reference pattern image;
- and
- superposing the random noise pattern image on the inspection reference pattern image.
An image correcting method for generating a correction image from an inspection reference pattern image and a pattern image under test, said method comprising:
- generating two random noise pattern images having grayscale values which are finer than the grayscale values of the two pattern images;
- and
- superposing the two random noise pattern images on the two pattern images, respectively.
An image correcting method for generating a correction image from an inspection reference pattern image and a pattern image under test, said method comprising:
- setting uninspected regions in the two pattern images;
- setting the grayscale values of the uninspected regions in the two pattern images as calibration minimum values;
- generating two random noise pattern images having grayscale values which are finer than the grayscale values of the two pattern images;
- and
- superposing the two random noise pattern images on the minimum calibration grayscale values in the two pattern images and the set uninspected regions, respectively.
An image correcting method for generating a correction image from an inspection reference pattern image and a pattern image under test, said method comprising:
- generating a random noise pattern image at least in a region having almost equal grayscale values in the inspection reference pattern image;
- superposing the random noise pattern image at least on the region having the almost equal grayscale values,
- the random noise pattern image having grayscale values which are finer than the grayscale values of the pattern images;
- generating simultaneous equations which describe an input-output relationship using, as an output, each pixel of the pattern image under test and using, as an input, a linear coupling of a pixel group around each corresponding pixel of the reference pattern image on which the random noise is superposed;
- solving the simultaneous equations to estimate parameters of the prediction model;
- and
- generating a correction image by using the estimated parameters.
An image correcting method for generating a correction image from an inspection reference pattern image and a pattern image under test, said method comprising:
- generating a random noise pattern image at least in a region having almost equal grayscale values in the inspection reference pattern image;
- superposing the random noise pattern image at least on the region having the almost equal grayscale values,
- the random noise pattern image having grayscale values which are finer than the grayscale values of the pattern images;
- setting reference points at a plurality of separated positions in an inspection reference pattern image on which the random noise is superposed, giving a weight to the inspection reference pattern image on which the random noise is superposed with reference to the reference points, and generating decomposed images the number of which is equal to the number of reference points;
- generating simultaneous equations which describe an input-output relationship using each pixel of the pattern image under test on which the random noise is superposed as an output and using a linear coupling of a pixel group around each corresponding pixel of the decomposed images the number of which is equal to the number of reference points as an input;
- solving the simultaneous equations to estimate parameters of the prediction model;
- and
- generating a correction image by using the estimated parameters.
Dependencies are inferred from the claim text.