Image conversion device, image conversion method, and recording medium

• US 20070172141A1
• Filed: 11/10/2006
• Published: 07/26/2007
• Est. Priority Date: 01/23/2006
• Status: Active Grant

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Bando, Yosuke
• Granted Patent: US 7,860,336 B2
• Time in Patent Office: Days
• US Class Current: 382/261
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: H04N 1/4092 Edge or detail enhancement

Abstract

An image conversion device according to an example of the invention comprises a blur estimating unit which estimates a blur state of input image data, a blur changing unit which changes the blur state estimated by the blur estimating unit into an arbitrary blur state, and an image constructing unit which constructs output image data on the basis of a blur changing result obtained by the blur changing unit.

Claims

1. An image conversion device comprising:

a blur estimating unit which estimates a blur state of input image data;

a blur changing unit which changes the blur state estimated by the blur estimating unit into an arbitrary blur state; and

an image constructing unit which constructs output image data on the basis of a blur changing result obtained by the blur changing unit.

2. The device according to claim 1, wherein

the blur estimating unit obtains a local blur state of the input image data, and

the blur changing unit changes the local blur state into an arbitrary local blur state.

3. The device according to claim 1, which further comprises

a separating unit which separates the input image data into shading image data and reflectance image data, and

a combining unit which generates output image data after combining on the basis of the output image data and the shading image data, and

in which the blur estimating unit estimates a blur state of the reflectance image data, and

the blur changing unit changes a blur state of the reflectance image data into an arbitrary blur state.

4. The device according to claim 1, which further comprises

an edge detecting unit which detects a position of an edge point and a direction of an edge of the input image data, and

a differentiation unit which calculates a luminance gradient of the input image data by differentiating the input image data, and

in which the blur estimating unit estimates an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point detected by the edge detecting unit, on the basis of the input image data and the direction of the edge,

the blur changing unit generates a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

the image constructing unit constructs the output image data on the basis of the luminance gradient after the blur change.

5. The device according to claim 1, which further comprises

an edge detecting unit which detects a position of an edge point and a direction of an edge of the input image data, and

a differentiating unit which calculates a luminance gradient of the input image data by differentiating the input image data, and

in which the blur estimating unit estimates an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point detected by the edge detecting unit, on the basis of the direction and the luminance gradient,

the blur changing unit generates a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

the image constructing unit constructs the output image data on the basis of the luminance gradient after the blur change.

6. The device according to claim 1, which further comprises

an edge detecting unit which detects a position of an edge point and a direction of an edge of input image data, and calculates a blurred luminance gradient of the input image data, and

a differentiating unit which calculates a luminance gradient of the input image data by differentiating the input image data, and

in which the blur estimating unit obtains a blur parameter for the blurred input image data which is included in a blur function representing the blur state, for the edge point detected by the edge detecting unit, on the basis of the direction and the blurred luminance gradient of the input image data, obtains an estimated blur parameter for the input image from the blur parameter, and estimates a local contrast of the edge,

the blur changing unit generates a luminance gradient after blur change of changing the estimated blur parameter into a desired blur parameter for the edge point, on the basis of the luminance gradient of the input image data, the direction, and the local contrast, and

the image constructing unit constructs the output image data on the basis of the luminance gradient after the blur change.

7. The device according to claim 6, wherein

the input image data is color image data comprising a plurality of components,

the edge detecting unit calculates a blurred luminance gradient for each of said plurality of components, and obtains the blurred luminance gradient of the input image data on the basis of the blurred luminance gradients of said plurality of components,

the differentiating unit calculates luminance gradients of said plurality of components,

the blur changing unit generates a luminance gradient after blur change for each of said plurality of components, which converts the estimated blur parameter into a desired blur parameter, for the edge point, on the basis of the luminance gradients, the direction, and the local contrast of said plurality of components, and

the image constructing unit constructs the output image data comprising image construction data for each of said plurality of components, on the basis of the luminance gradient after blur change for each of said plurality of components.

8. An image conversion method comprising:

estimating a blur state of input image data;

changing the blur state into an arbitrary blur state; and

constructing output image data on the basis of a blur changing result obtained by the changing.

9. A method according to claim 8, wherein

estimating comprises obtaining a local blur state of the input image data, and

changing comprises changing the local blur state into an arbitrary local blur state.

10. The method according to claim 8, which further comprises

separating the input image data into shading image data and reflectance image data, and

generating output image data after combining on the basis of the output image data and the shading image data, and

in which estimating comprises estimating a blur state of the reflectance image data, and

changing comprises changing a blur state of the reflectance image data into an arbitrary blur state.

11. The method according to claim 8, which further comprises

detecting a position of an edge point and a direction of an edge of the input image data, and

calculating a luminance gradient of the input image data by differentiating the input image data, and

in which estimating comprises estimating an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point, on the basis of the input image data and the direction of the edge,

changing comprises generating a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

constructing comprises constructing the output image data on the basis of the luminance gradient after the blur change.

12. The method according to claim 8, which further comprises

detecting a position of an edge point and a direction of an edge of the input image data, and

calculating a luminance gradient of the input image data by differentiating the input image data, and

in which estimating comprises estimating an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point, on the basis of the direction and the luminance gradient,

changing comprises generating a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

constructing comprises constructing the output image data on the basis of the luminance gradient after the blur change.

13. The method according to claim 8, which further comprises

detecting a position of an edge point and a direction of an edge of input image data, and calculating a blurred luminance gradient of the input image data, and

calculating a luminance gradient of the input image data by differentiating the input image data, and

in which estimating comprises obtaining a blur parameter for the blurred input image data which is included in a blur function representing the blur state, for the edge point, on the basis of the direction and the blurred luminance gradient of the input image data, obtaining an estimated blur parameter for the input image from the blur parameter, and estimating a local contrast of the edge,

changing comprises generating a luminance gradient after blur change of changing the estimated blur parameter into a desired blur parameter for the edge point, on the basis of the luminance gradient of the input image data, the direction, and the local contrast, and

constructing comprises constructing the output image data on the basis of the luminance gradient after the blur change.

14. The method according to claim 13, wherein

the input image data is color image data comprising a plurality of components,

calculating the blurred luminance gradient of input image data comprises calculating a blurred luminance gradient for each of said plurality of components, and obtaining the blurred luminance gradient of the input image data on the basis of the blurred luminance gradients of said plurality of components,

calculating the luminance gradient of the input image data comprises calculating luminance gradients of said plurality of components,

changing comprises generating a luminance gradient after blur change for each of said plurality of components, which converts the estimated blur parameter into a desired blur parameter, for the edge point, on the basis of the luminance gradients, the direction, and the local contrast of said plurality of components, and

constructing comprises constructing the output image data comprising image construction data for each of said plurality of components, on the basis of the luminance gradient after blur change for each of said plurality of components.

15. A recording medium comprising:

a first computer readable code configured to estimate a blur state of input image data;

a second computer readable code configured to change the blur state estimated by the blur estimating unit into an arbitrary blur state; and

a third computer readable code configured to construct output image data on the basis of a blur changing result obtained by the blur changing unit.

16. The recording medium according to claim 15, wherein

the first computer readable code obtains a local blur state of the input image data, and

the second computer readable code changes the local blur state into an arbitrary local blur state.

17. The recording medium according to claim 15, which further comprises

a fourth computer readable code configured to detect a position of an edge point and a direction of an edge of the input image data, and

a fifth computer readable code configured to calculate a luminance gradient of the input image data by differentiating the input image data, and

in which the first computer readable code estimates an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point, on the basis of the input image data and the direction of the edge,

the second computer readable code generates a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

the third computer readable code constructs the output image data on the basis of the luminance gradient after the blur change.

18. The recording medium according to claim 15, which further comprises

a fourth computer readable code configured to detect a position of an edge point and a direction of an edge of the input image data, and

a fifth computer readable code configured to calculate a luminance gradient of the input image data by differentiating the input image data, and

in which the first computer readable code estimates an estimated blur parameter and a local contrast of the edge included in a blur function representing the blur state, for the edge point, on the basis of the direction and the luminance gradient,

the second computer readable code generates a luminance gradient for the edge point after blur change of changing the estimated blur parameter into a desired blur parameter, on the basis of the luminance gradient, the direction, and the local contrast, and

the third computer readable code constructs the output image data on the basis of the luminance gradient after the blur change.

19. The recording medium according to claim 15, which further comprises

a fourth computer readable code configured to detect a position of an edge point and a direction of an edge of input image data, and calculate a blurred luminance gradient of the input image data, and

a fifth computer readable code configured to calculate a luminance gradient of the input image data by differentiating the input image data, and

in which the first computer readable code obtains a blur parameter for the blurred input image data which is included in a blur function representing the blur state, for the edge point, on the basis of the direction and the blurred luminance gradient of the input image data, obtains an estimated blur parameter for the input image from the blur parameter, and estimates a local contrast of the edge,

the second computer readable code generates a luminance gradient after blur change of changing the estimated blur parameter into a desired blur parameter for the edge point, on the basis of the luminance gradient of the input image data, the direction, and the local contrast, and

the third computer readable code constructs the output image data on the basis of the luminance gradient after the blur change.

20. The recording medium according to claim 19, wherein

the input image data is color image data comprising a plurality of components,

the fourth computer readable code calculates a blurred luminance gradient for each of said plurality of components, and obtains the blurred luminance gradient of the input image data on the basis of the blurred luminance gradients of said plurality of components,

the fifth computer readable code calculates luminance gradients of said plurality of components,

the second computer readable code generates a luminance gradient after blur change for each of said plurality of components, which converts the estimated blur parameter into a desired blur parameter, for the edge point, on the basis of the luminance gradients, the direction, and the local contrast of said plurality of components, and

the third computer readable code constructs the output image data comprising image construction data for each of said plurality of components, on the basis of the luminance gradient after blur change for each of said plurality of components.