RESTORATION METHOD FOR BLURRED IMAGES USING BI-LEVEL REGIONS

• US 20100183241A1
• Filed: 11/17/2009
• Published: 07/22/2010
• Est. Priority Date: 01/21/2009
• Status: Abandoned Application

• Current Assignee: Novatek Microelectronics Corporation (Novatek Microelectronics Corp Limited)
• Original Assignee: Novatek Microelectronics Corporation (Novatek Microelectronics Corp Limited)
• Inventors: Peng, Yu-Chun, Lin, Yu-Mo, Huang, Po-Hao, Lai, Shang-Hong, Huang, Chih-Chih, Yu, Shu-Han
• Application Number:
  US12/619,766
• Publication Number:
  US 20100183241A1
• Time in Patent Office: Days
• US Class Current: 382/270
• CPC Class Codes: G06T 2207/20201 Motion blur correction
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: G06T 7/136 involving thresholding

Abstract

A blind image restoration method restores a motion blurred image and a blur kernel is estimated based on an intrinsic bi-level image region of the motion blurred image. In addition, the blur kernel is iteratively estimated. When the blur kernel is iteratively estimated, bi-level image priors are introduced to achieve better image restoration.

Claims

1. An image restoration method applied to an image acquisition device, the method comprising:

receiving a blurred image;

selecting at least one first image region of the blurred image;

performing thresholding and brightness compensation on the first image region to obtain a second image region;

estimating a blur kernel of the blurred image based on the first image region, the second image region and a first image prior;

restoring the second image region based on the blur kernel, a second image prior and a third image prior; and

restoring the blurred image based on the blur kernel and the third image prior and outputting the restored blurred image if the restored second image region is converged.

2. The method according to claim 1, wherein the thresholding step comprises:

resetting intensity values of all pixels in the first image region based on a first threshold value, wherein;

the intensity values of the pixels lower than the first threshold value are reset as a first value; and

the intensity values of the pixels higher than the first threshold value are reset as a second value.

3. The method according to claim 1, wherein the blur kernel is a two-dimensional gray-level image and represents a camera shake track.

4. The method according to claim 1, further comprising:

setting the blur kernel and the restored second image region are independent from each other.

5. The method according to claim 1, wherein the first image prior comprises a kernel prior, the second image prior comprises a bi-level prior, and the third image prior comprises a sparse prior.

6. The method according to claim 1, wherein the step of restoring the second image region comprises:

determining a likelihood of the blurred image according to an image noise if the blur kernel and the restored second image region are known.

7. The method according to claim 1, wherein the blurred image is represented by a convolution of the restored second image region with the blur kernel.

8. The method according to claim 1, further comprising:

normalizing the restored second image region to determine the second image prior.

9. The method according to claim 1, further comprising:

obtaining an optimum restored second image region if the blur kernel is assumed to be known; and

obtaining an optimum blur kernel if the restored second image region is assumed to be known.

10. The method according to claim 1, further comprising:

if the restored second image region is not converged yet, iteratively estimating the blur kernel until the restored second image region is converged.