Blur image adjusting method

• US 8,139,884 B2
• Filed: 09/26/2008
• Issued: 03/20/2012
• Est. Priority Date: 01/24/2008
• Status: Active Grant

• Current Assignee: ASUSTek Computer, Inc.
• Original Assignee: ASUSTek Computer, Inc.
• Inventors: Chien, Yen-Lung, Shen, Chih-Tsung
• Primary Examiner(s): Ahmed, Samir
• Assistant Examiner(s): Liu, Li
• Application Number:
  US12/238,513
• Publication Number:
  US 20090190851A1
• Time in Patent Office: 1,271 Days
• Field of Search: None
• US Class Current: 382/255
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: H04N 23/68 for stable pick-up of the scene, e.g. compensating for camera body vibrations
• CPC Class Codes: H04N 23/80 Camera processing pipelines; Components thereof

Abstract

A blur image adjusting method includes the following steps. Firstly, a blur image in YCbCr color space is obtained. The Y component of the blur image is extracted so as to obtain a Y component blur image. A blur area is extracted from the Y component blur image by an edge detection technology. A horizontal shift amount and a vertical shift amount are estimated according to a horizontal shift pixel number distribution and a vertical shift pixel number distribution of the blur area. A point spread function is determined according to the horizontal shift amount and the vertical shift amount. Afterwards, the blur image is adjusted according to the point spread function.

Claims

1. A blur image adjusting method, comprising steps of:

obtaining a blur image in a YCbCr color space;

extracting the Y component of the blur image so as to obtain a Y component blur image;

extracting a blur area from the Y component blur image by an edge detection technology;

estimating a horizontal shift amount and a vertical shift amount according to a horizontal shift pixel number distribution and a vertical shift pixel number distribution of the blur area;

determining a point spread function according to the horizontal shift amount and the vertical shift amount; and

adjusting the blur image according to the point spread function.

2. The blur image adjusting method according to claim 1 further comprising a step of converting the blur image in a RGB color space into the blur image in the YCbCr color space before the blur image in the YCbCr color space is obtained.

3. The blur image adjusting method according to claim 1 wherein the edge detection technology is a Sobel edge detection technology.

4. The blur image adjusting method according to claim 1 wherein the horizontal shift pixel number distribution indicates occurrence count of various horizontal shift pixel numbers of whole black lines contained in the blur area from left to right.

5. The blur image adjusting method according to claim 1 wherein the vertical shift pixel number distribution indicates occurrence count of various vertical shift pixel numbers of whole black lines contained in the blur area from top to bottom.

6. The blur image adjusting method according to claim 1 wherein the step of adjusting the blur image according to the point spread function includes designing a restoration filter according to the point spread function, thereby recovering a sharp image from the blur image.

7. The blur image adjusting method according to claim 6 wherein the restoration filter is designed by using a Lucy-Richardson algorithm.

8. The blur image adjusting method according to claim 6 wherein the restoration filter is a Wiener filter.

9. The blur image adjusting method according to claim 1 wherein the blur image is captured by a charge coupled device.