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Blind camera shake deblurring method based on L0 sparse prior

A sparse prior, camera shake technology, applied in image data processing, instruments, calculations, etc., can solve problems such as the inability to guarantee the optimality of the solution, lack of optimization theoretical support, etc., and achieve high-quality deblurring.

Active Publication Date: 2013-11-27
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, the current maximum a posteriori estimation method often uses the smoothing filter and the impact filter to predict the edge information of the image, and then uses the predicted edge image to estimate the blur kernel. After repeated iterations of these two processes, the blur kernel is finally estimated. Strict optimization theory support, so the (local) optimality of the solution cannot be guaranteed

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  • Blind camera shake deblurring method based on L0 sparse prior
  • Blind camera shake deblurring method based on L0 sparse prior
  • Blind camera shake deblurring method based on L0 sparse prior

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Embodiment Construction

[0093] (1) Using the first-order derivative operators in the horizontal and vertical directions▽ h =[1,-1;0,0],▽ v =[1,0;-1,0], use the MATLAB function conv2 to obtain the gradient image of the camera shake blurred image y y d = ▿ d ⊗ y , d ∈ Λ , Λ = { h , v } :

[0094] the y h =conv2(y,▽ h ,'valid');

[0095] the y v =conv2(y,▽ v ,'valid');

[0096] (2) Let the size of the fuzzy kernel k to be estimated be Z×Z, in order to improve the convergence of the fuzzy kernel estimation method, a multi-scale implementation method is used to iteratively estimate the fuzzy kernel;

[0097] (3) Let the initial blur kernel k (1) =[0,0,0;1,1,1;0,0,0]3 (dimensions 3×3), and use the following MATLAB code to determine the total scale

[0098] The numb...

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Abstract

The invention discloses a blind camera shake deblurring method based on the L0 sparse prior, and belongs to the technical field of digital image processing. The blind camera shake deblurring method is a method for deblurring blurred images caused by camera shaking, and various space-unchanged camera shaking blurred kernels, namely the point spread functions, can be estimated. The blind camera shake deblurring method solves the problem that a current variational bayes estimation method is high in computing complexity and solves the problem that a current maximum posteriori estimation method lacks strict optimization theory supports. The blind camera shake deblurring method comprises the steps of firstly, introducing remarkable edge sparse prior based on the L0 norm, and using the iterative hard threshold compressed method to achieve recessive automatic prediction of remarkable edge characteristics, secondly, introducing camera shake blurred kernel sparse prior, and using the iterative repeated weighted least square method to achieve rapid estimation of the blurred kernels, and finally, using the image non-blind deblurring method based on super-Laplacian prior to obtain a high-quality deblurred image. The flow diagram of the blind camera shake deblurring method is shown in the figure 1.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to the field of deblurring blurred images caused by camera shaking. Background technique [0002] Blind camera shake deblurring refers to the removal or reduction of image motion blur that occurs during the process of shooting digital images with a camera. It is a very important and challenging research content in digital image processing in recent years. Its core is to estimate the corresponding camera shake The blur kernel (point spread function). Currently, researchers have proposed a number of different methods. [0003] The most classic blind camera shake deblurring method is the maximum likelihood estimation method, which has been integrated into the image processing toolbox of the numerical calculation software MATLAB. High signal-to-noise ratio, and requires a small size of the blur kernel. Another disadvantage of this method is that the detailed informat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/20
Inventor 邵文泽
Owner NANJING UNIV OF POSTS & TELECOMM
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