SYSTEM AND METHOD FOR MULTI-RESOLUTION SHARPNESS TRANSPORT ACROSS COLOR CHANNELS

• US 20120120245A1
• Filed: 11/15/2010
• Published: 05/17/2012
• Est. Priority Date: 11/15/2010
• Status: Active Grant

• Current Assignee: Intuitive Surgical Operations, Inc. (Intuitive Surgical Holdings, LLC)
• Original Assignee: Intuitive Surgical Operations, Inc. (Intuitive Surgical Holdings, LLC)
• Inventors: Zhao, Wenyi, DiMaio, Simon P., Scott, David D.
• Granted Patent: US 9,697,588 B2
• Time in Patent Office: Days
• US Class Current: 348/164
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20212 Image combination
• CPC Class Codes: G06T 5/10 using non-spatial domain filtering
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening

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.

Claims

1. An image sharpening method comprising:

capturing an image;

decomposing the image into a plurality of image-representation components;

transforming each image-representation component 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 sharpness information 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;

transforming the sharpened multi-resolution representation of the second one of the image-representation components to obtain a sharpened image; and

displaying the sharpened image.

2. The method of claim 1:

wherein capturing the image comprises illuminating a scene to be imaged with narrow band illumination.

3. The method of claim 1:

wherein capturing the image comprises illuminating a scene to be imaged with infrared illumination.

4. The method of claim 1:

wherein capturing the image comprises illuminating a scene to be imaged with wide band illumination.

5. The method of claim 1:

wherein capturing the image comprises illuminating a scene to be imaged with X-Ray.

6. The method of claim 1:

wherein capturing the image comprises using a single image capture area on an integrated circuit device to capture the image.

7. the method of claim 1:

wherein capturing the image comprises using a plurality of integrated circuit devices in a single camera to capture the image.

8. The method of claim 1:

wherein capturing the image comprises using a plurality of cameras to capture the image.

9. The method of claim 8:

wherein aligning image components is performed.

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 a first one of the image-representation components comprises information from a near infrared spectrum feature of the image and a second one of the 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 image-representation components to a second transformation level representation of the unsharpened multi-resolution representation of the second one of the image-representation components to create the sharpened multi-resolution representation of the second one of the 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 eigen values.

23. The method of claim 1:

wherein the sharpness information comprises the sharpest sharpness information selected from each of the unsharpened multi-resolution representations for each image-representation component.

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 image-representation components and the sharpened multi-resolution representation of the second one of the 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 sharpened second image representation component comprises a weighted sum that includes the unsharpened multi-resolution representation for the first one of the image representation components and the unsharpened multi-resolution representation for the second one of the image representation components.

28. The method of claim 1, further comprising:

selecting a first sharpness state or a second 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 image-representation components.