System and method for multi-resolution sharpness transport across color channels

Patent metadata

Field	Value
Publication number	US-9697588-B2
Application number	US-94663410-A
Country	US
Kind code	B2
Filing date	Nov 15, 2010
Priority date	Nov 15, 2010
Publication date	Jul 4, 2017
Grant date	Jul 4, 2017

Abstract

Provided are a system and method for image sharpening is provided that involves capturing an image, and then decomposing the image into a plurality of image-representation components, such as RGB components for example. Each image-representation component is transformed to obtain an unsharpened multi-resolution representation for each image-representation component. A multi-resolution representation includes a plurality of transformation level representations. Sharpness information is transported from an unsharpened transformation level representation of a first one of the image-representation components to a transformation level representation of an unsharpened multi-resolution representation of a second one of the image-representation components to create a sharpened multi-resolution representation of the second one of the image-representation components. The sharpened multi-resolution representation of the second one of the image-representation components is then transformed to obtain a sharpened image. The improved and sharpened image may then be displayed.

First claim

We claim:

1. An image sharpening method comprising:
capturing an image;
decomposing, by an image system, the image into a plurality of image-representation components;
transforming, by the image system, each image-representation component of the plurality of image-representation components to obtain an unsharpened multi-resolution representation for each image-representation component, wherein a multi-resolution representation comprises a plurality of transformation level representations;
transporting, by the image system, sharpness information from an unsharpened transformation level representation of a first one of the plurality of image-representation components to a same transformation level representation of an unsharpened multi-resolution representation of a second one of the plurality of image-representation components to create a sharpened multi-resolution representation of the second one of the image-representation components, wherein the transported sharpness information modifies sharpness information in the same transformation level representation of the unsharpened multi-resolution representation of the second one of the plurality of image-representation components;
transforming, by the image system, the sharpened multi-resolution representation of the second one of the plurality of image-representation components to obtain a sharpened image; and
displaying the sharpened image on a display device.

2. The method of claim 1 :
wherein the capturing the image comprises illuminating a scene to be imaged with narrow band illumination.

3. The method of claim 1 :
wherein the capturing the image comprises illuminating a scene to be imaged with infrared illumination.

4. The method of claim 1 :
wherein the capturing the image comprises illuminating a scene to be imaged with wide band illumination.

5. The method of claim 1 :
wherein the capturing the image comprises illuminating a scene to be imaged with X-Ray illumination.

6. The method of claim 1 :
wherein the capturing the image comprises capturing the image with a single image capture area on an integrated circuit device.

7. The method of claim 1 :
wherein the capturing the image comprises capturing the image with a plurality of integrated circuit devices in a single camera.

8. The method of claim 1 :
wherein the capturing the image comprises capturing each image component of the image with a different camera in a plurality of cameras.

9. The method of claim 8 , the capturing the image further comprising:
aligning the image components captured with the plurality of cameras.

10. The method of claim 1 :
wherein the image comprises near infrared spectrum features and visible spectrum features.

11. The method of claim 1 :
wherein the image comprises X-Ray.

12. The method of claim 1 :
wherein decomposing the image into a plurality of image-representation components comprises performing a color space transform.

13. The method of claim 12 :
wherein performing the color space transform comprises transforming RGB image-representation components to YCbCr image-representation components.

14. The method of claim 1 :
wherein the plurality of image-representation components comprises RGB image-representation components.

15. The method of claim 1 :
wherein one of the plurality of image-representation components comprises information from a near infrared spectrum feature of the image and another one of the plurality of image-representation components comprises information from a visible spectrum feature of the image.

16. The method of claim 1 :
wherein the transformation level representations comprise Laplacian representations.

17. The method of claim 1 :
wherein the transformation level representations comprise wavelet representations.

18. The method of claim 1 further comprising:
transporting sharpness information from a second unsharpened transformation level representation of the first one of the plurality of image-representation components to a second transformation level representation of the unsharpened multi-resolution representation of the second one of the plurality of image-representation components to create the sharpened multi-resolution representation of the second one of the plurality of image-representation components.

19. The method of claim 1 :
wherein the sharpness information is image-driven.

20. The method of claim 19 :
wherein the image-driven sharpness information is gradient-based.

21. The method of claim 19 :
wherein the image-driven sharpness information is based on local statistics.

22. The method of claim 21 :
wherein the local statistics comprise kurtosis and/or eigenvalues.

23. The method of claim 1 :
wherein the sharpness information comprises sharpest sharpness information selected from each of the unsharpened multi-resolution representations for each image-representation component of the plurality of image-representation components.

24. The method of claim 1 :
wherein the sharpened image comprises an RGB image.

25. The method of claim 1 , further comprising:
transforming the unsharpened multi-resolution representation for the first one of the plurality of image-representation components and the sharpened multi-resolution representation of the second one of the plurality of image-representation components to obtain the sharpened image.

26. The method of claim 25 :
wherein the sharpened image comprises an RGB image.

27. The method of claim 1 :
wherein the sharpness information in the transformation level of the sharpened multi-resolution representation of the second one of the plurality of image-representation components comprises a weighted sum that includes the sharpness information from the unsharpened multi-resolution representation for the first one of the image representation components and sharpness information from the unsharpened multi-resolution representation for the second one of the image representation components.

28. The method of claim 1 , further comprising:
selecting, by the image system, a first sharpness state or a second sharpness state of the sharpened image in response to a sharpness selection input;
wherein for the first sharpness state, sharpness information is transported from a first number of unsharpened transformation level representations; and
wherein for the second sharpness state, sharpness information is transported from a second number, different from the first number, of unsharpened transformation level representations.

29. The method of claim 1 :
wherein the transformation level representations comprise Laplacian transformation level representations; and
wherein the sharpness information comprises an absolute value of pixel values in the unsharpened transformation level representation of the first one of the plurality of image-representation components.

Assignees

• Zhao Wenyi
• Dimaio Simon P
• Scott David D
• Intuitive Surgical Operations

Inventors

• Zhao Wenyi
• Dimaio Simon P
• Scott David D

Classifications

• G06T2207/20212

  Image combination · CPC title

• G06T2207/10024

  Color image · CPC title

• G06T2207/20016

  Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform · CPC title

• G06T5/10

  using non-spatial domain filtering · CPC title

• G06T5/003 Primary

  Physics · mapped topic