Systems and Methods for Defect Detection Using Image Reconstruction

Patent metadata

Field	Value
Publication number	US-2017191945-A1
Application number	US-201615357888-A
Country	US
Kind code	A1
Filing date	Nov 21, 2016
Priority date	Jan 1, 2016
Publication date	Jul 6, 2017
Grant date	—

Abstract

An inspection system includes an illumination sub-system, a collection sub-system, and a controller. The illumination sub-system includes an illumination source configured to generate a beam of illumination and a set of illumination optics to direct the beam of illumination to a sample. The a collection sub-system includes a set of collection optics to collect illumination emanating from the sample and a detector configured to receive the collected illumination from the sample. The controller is configured to acquire a test image of the sample, reconstruct the test image to enhance the resolution of the test image, and detect one or more defects on the sample based on the reconstructed test image.

First claim

What is claimed:

1 . An inspection system, comprising:
an illumination sub-system, comprising:
an illumination source configured to generate a beam of illumination; and
a set of illumination optics to direct the beam of illumination to a sample;
a collection sub-system, comprising:
a set of collection optics to collect illumination emanating from the sample; and
a detector configured to receive the collected illumination from the sample; and
a controller communicatively coupled to the detector, the controller including a memory device and one or more processors configured to execute program instructions configured to cause the one or more processors to:
acquire a test image of the sample;
reconstruct the test image to enhance the resolution of the test image; and
detect one or more defects on the sample based on the reconstructed test image.

2 . The inspection system of claim 1 , further comprising:
estimating a point spread function of the inspection system.

3 . The inspection system of claim 2 , wherein estimating a point spread function of the inspection system comprises:
estimating the point spread function of the inspection system as a Fourier transform of a linear combination of an illumination aperture and a collection aperture of the inspection system.

4 . The inspection system of claim 2 , wherein reconstructing the test image comprises:
deconvolving the test image based on the estimated point spread function.

5 . The inspection system of claim 4 , wherein deconvolving the test image comprises:
deconvolving the test image using at least one of direct inversion, a Wiener filter, maximum likelihood deconvolution, or maximum a posterior deconvolution.

6 . The inspection system of claim 5 , wherein deconvolving the test image using maximum likelihood deconvolution comprises:
deconvolving the test image using noise having at least one of a Gaussian or a Poisson distribution.

7 . The inspection system of claim 6 , wherein deconvolving the test image using maximum likelihood deconvolution comprises:
deconvolving the test image using Richardson-Lucy deconvolution based on the estimated point spread function.

8 . The inspection system of claim 5 , wherein deconvolving the test image using maximum a posterior deconvolution comprises:
deconvolving the test image using noise having at least one of a Gaussian or a Poisson distribution.

9 . The inspection system of claim 4 , wherein a cost function associated with deconvolving the test image includes a sparse distribution regularization parameter.

10 . The inspection system of claim 9 , wherein a cost function associated with deconvolving the test image further includes an image gradient regularization parameter.

11 . The inspection system of claim 10 , wherein the image gradient regularization parameter comprises:
at least one of a Total Variation regularization parameter, a Tikhonov-Miller regularization parameter, or a Bilateral regularization parameter.

12 . The inspection system of claim 10 , wherein detecting one or more defects on the sample based on the reconstructed test image comprises:
acquiring a reference image of the sample; deconvolving the reference image based on the point spread function; generating a difference image between the deconvolved test image and the deconvolved reference image; and detecting one or more defects on the sample based on the difference image.

13 . The inspection system of claim 12 , wherein a cost function associated with deconvolving the reference image includes the image gradient distribution regularization parameter.

14 . The inspection system of claim 1 , wherein acquiring the test image of the sample includes acquiring the test image of the sample using an anti-aliasing technique, wherein the anti-aliasing technique suppresses aliasing noise in the test image, wherein reconstructing the test image to enhance the resolution of the test image recovers one or more spatial frequencies associated with the sample impacted by the anti-aliasing technique.

15 . The inspection system of claim 14 , wherein reconstructing the test image comprises:
interpolating the test image.

16 . The inspection system of claim 15 , wherein interpolating the test image comprises:
interpolating the test image using at least one of bilinear interpolation, cubic interpolation, Lanczos interpolation, nearest neighbor interpolation, B-spline interpolation, or sinc interpolation.

17 . The inspection system of claim 14 , wherein reconstructing the test image comprises:
estimating a point spread function of the inspection system; and deconvolving the test image based on the estimated point spread function.

18 . The inspection system of claim 1 , wherein detecting one or more defects on the sample based on the reconstructed test image includes reporting one or more locations of the one or more defects on the sample.

19 . An inspection system, comprising:
an illumination sub-system, comprising:
an illumination source configured to generate a beam of illumination; and
a set of illumination optics to direct the beam of illumination to a sample;
a collection sub-system, comprising:
a set of collection optics to collect illumination emanating from the sample; and
a detector configured to receive the collected illumination from the sample; and
a controller communicatively coupled to the detector, the controller including a memory device and one or more processors configured to execute program instructions configured to cause the one or more processors to:
acquire a test image of the sample;
detect one or more defects on the sample based on the test image;
generate one or more patch images associated with the one or more detected defects on the sample;
reconstruct the one or more patch images to enhance the resolution of the one or more patch images; and
classify the one or more defects based on the one or more reconstructed patch images.

20 . The inspection system of claim 19 , wherein reconstructing the test image comprises:
estimating a point spread function of the inspection system; and deconvolving the one or more patch images based on the estimated point spread function.

21 . A multi-mode inspection system, comprising:
an illumination sub-system, comprising:
an illumination source configured to generate two or more modes of illumination; and
a set of illumination optics to sequentially direct the two or more modes of illumination to a sample;
a collection sub-system, comprising:
a set of collection optics to collect illumination emanating from the sample, wherein the set of collection optics includes an adjustable collection aperture, wherein the adjustable collection aperture is configured to generate two or more collection modes, wherein the illumination sub-system includes two or more system modes formed from the two or more modes of illumination and the two or more collection modes; and
a detector configured to receive the collected illumination from the sample; and
a controller communicatively coupled to the detector, the controller including a memory device and one or more processors configured to execute program instructions configured to cause the one or more processors to:
acquire two or more test images of the sample based on the two or more system modes;
estimate a point spread function of the inspection system;
reconstruct the two or more test images to enhance the resolution of the two or more test

Assignees

• Kla Tencor Corp

Inventors

• Zhang Jing
• Nesbitt Jeremy
• Chen Grace Hsiu-Ling
• Wallingford Richard

Classifications

• G06T2207/10056

  Microscopic image · CPC title

• G06T2207/20076

  Probabilistic image processing · CPC title

• G06T2207/20056

  Discrete and fast Fourier transform, [DFT, FFT] · CPC title

• G06T7/001

  using an image reference approach · CPC title

• G06T7/0006

  using a design-rule based approach · CPC title