Spatial standard observer

• US 20100329585A1
• Filed: 08/09/2010
• Published: 12/30/2010
• Est. Priority Date: 01/24/2005
• Status: Active Grant

• Current Assignee: Space Administration, The Government Of The United States Of America, As Represented By The Secretary Of The Navy
• Original Assignee: Space Administration, The Government Of The United States Of America, As Represented By The Secretary Of The Navy
• Inventors: Watson, Andrew B.
• Granted Patent: US 8,139,892 B2
• Time in Patent Office: Days
• US Class Current: 382/279
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: H04N 17/04 for receivers
• CPC Class Codes: H04N 19/60 using transform coding
• CPC Class Codes: H04N 19/86 involving reduction of coding artifacts, e.g. of blockiness

Abstract

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image, or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image. Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer, SSO. Some embodiments include masking functions, window functions, special treatment for images lying on or near borders and pre-processing of test images.

Claims

1. A method of processing an image, the method comprising:

producing a test image;

producing a reference image;

producing a test contrast image in the absence of temporal filtering;

producing a reference contrast image;

producing a difference image; and

producing a just noticeable difference image as a mathematical combination of the difference image.

2. The method of claim 1, wherein a reference luminance image is produced from the reference image and a test luminance image is produced from the test image.

3. The method of claim 2, wherein a local mean luminance reference image is produced as a convolution of the reference luminance image and a luminance filter function.

4. The method of claim 3, wherein the convolution is defined as confined convolution, the method comprising:

receiving an image,

padding the image with zeros to provide a first intermediate image,

convolving the first intermediate image with a selected non-negative kernel function to obtain a second intermediate image,

cropping the second intermediate image to obtain a third intermediate image.

5. The method of claim 4, further comprising receiving said third intermediate image, I3(x,y)=PCC{K(x,y),I(x,y)} and forming a fourth intermediate image, defined as I4(x,y)=K(x,y) (c) I(x,y)=PCC{K(x,y), I(x,y))/PCC{K(x,y)/Σ

xΣ

yK(x,y),I(x,y)}.

6. The method of claim 3, wherein the test contrast image is produced by a mathematical combination of the test luminance image and the local mean luminance reference image.

7. The method of claim 3, wherein the test contrast image is produced by a mathematical combination of the test luminance image, the local mean luminance reference image and a border aperture function.

8. The method of claim 3, wherein the test contrast image is produced by a mathematical combination of a test luminance image, the local mean luminance reference image and an image of a border surrounding the reference image.

9. The method of claim 3, wherein the reference contrast image is produced by a mathematical combination of the reference luminance image and the local mean luminance reference image.

10. The method of claim 3, wherein the reference contrast image is produced by a mathematical combination of the reference luminance image, the local mean luminance reference image and a border aperture function.

11. The method of claim 1, wherein the just noticeable difference image is produced as a mathematical combination of the difference image with a window function.

12. The method of claim 11, wherein the window function is convolved with the difference image.

13. The method of claim 12, wherein the convolution is defined as confined convolution.

14. The method of claim 1, wherein the difference image is produced by subtracting the reference image from the test image to produce the difference image.

15. The method of claim 1, wherein a contrast sensitivity filter is applied to the test contrast image to produce a filtered test image.

16. The method of claim 13, wherein the contrast sensitivity filter is applied to the reference contrast image to produce a filtered reference image.

17. The method of claim 14, wherein the difference image is produced by subtracting the filtered reference image from the filtered test image to produce the difference image.

18. The method of claim 1, wherein the test contrast image is produced by producing a mask image as a mathematical combination of the reference image with a masking filter, and producing a difference image as a ratio of the difference image and the mask image.

19. The method of claim 16, wherein the test contrast image is produced by producing a mask image as a mathematical combination of the filtered reference image with a masking filter, and producing a difference image as a ratio of the difference image and the mask image.

20. The method of claim 1, where in a visibility metric is produced by pooling the just noticeable difference image.

21. The method of:

claim 20, wherein the process of pooling combines the values of the pixels in the x and y directions of the just noticeable difference image to produce a single just noticeable difference value.

22. The method of claim 1, further comprising preprocessing at least one of the test image and the reference image by downsampling.

23. The method of claim 1, further comprising preprocessing at least one of the test image and the reference image by convolution with a selected pre-filtering function.

24. The method of claim 22, wherein the convolution is defined as confined convolution.

25. The method of claim 1, further comprising preprocessing, by cropping, at least one of the test image and the reference image.

26. A method of claim 1, wherein the reference image is produced from the test image, the method comprising:

providing the test image having first and second opposing sides of the image

performing a convolution of the test image with a selected filter that isolates the first and second opposing sides of the image from each other, to thereby form the reference image.

27. The method of claim 26, wherein the convolution is defined as confined convolution.

29. The method of claim 27, further comprising receiving said third intermediate image, I3(x,y)=PCC{K(x,y),I(x,y)} and forming a fourth intermediate image, defined as I4(x,y)=K(x,y) I(x,y)=PCC{K(x,y), I(x,y))/PCC(K(x,y)/ExEyK(x,y),I(x,y)}.

28. A method of performing confined convolution, the method comprising:

receiving an image,

padding the image with zeros to provide a first intermediate image,

convolving the first intermediate image with a selected non-negative kernel function to obtain a second intermediate image,

cropping the second intermediate image to obtain a third intermediate image.

30. A method of processing an image, the method comprising:

producing a test image;

producing a reference image from the test image;

producing a test contrast image;

producing a reference contrast image;

producing a difference image; and

producing a just noticeable difference image as a mathematical combination of the difference image.

31. A method of processing an image, the method comprising:

producing a test image;

producing a reference image;

producing a local mean luminance reference image as a convolution of a reference luminance image and a luminance filter function;

producing a test contrast image;

producing a reference contrast image;

producing a difference image; and

producing a just noticeable difference image as a mathematical combination of the difference image.

33. The method of claim 31, wherein the window function is convolved with the difference image.

34. The method of claim 33, wherein the convolution is defined as confined convolution.

32. A method of processing an image, the method comprising:

producing a test image;

producing a reference image;

producing a test contrast image;

producing a reference contrast image;

producing a difference image; and

producing a just noticeable difference image as a mathematical combination of the difference image with a window function.