Multi-scale non-local regularization blurring kernel estimation method

A fuzzy kernel, non-local technology, applied in computing, image data processing, instruments, etc., can solve problems such as insufficient prior knowledge of images

Active Publication Date: 2015-05-06
XIDIAN UNIV
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Problems solved by technology

However, the prior knowledge of the i...

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  • Multi-scale non-local regularization blurring kernel estimation method
  • Multi-scale non-local regularization blurring kernel estimation method
  • Multi-scale non-local regularization blurring kernel estimation method

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Embodiment Construction

[0032] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0033] Step 1: Blur the blurred image y to be processed 4 times with a Gaussian blur kernel whose size is k_size_guess×k_size_guess and standard deviation is k_size_guess / 6, and the processed image is denoted as y 0 , to smooth the noise effect in the image;

[0034] Step 2: Compute the image y indicating the processed image in step 1 0 The map of the gradient edge of

[0035] 2a) Use a Gaussian blur of size 3×3 with a standard deviation of 0.5 to check the image y after step 1 0 Perform filtering to obtain a filtered image;

[0036] 2b) calculating the horizontal and vertical gradient images gx and gy of the filtered image in step 2a) respectively;

[0037] 2c) Use a 11×11 identity matrix h2 to filter the gradient images gx and gy respectively to generate new gradient images gx_sum and gy_sum;

[0038] 2d) Calculate the top matrix, top is the product of gx_sum and its...

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Abstract

The invention discloses a multi-scale non-local regularization blurring kernel estimation method. In image based blind de-blurring problems, posterior sharp images and blurring kernels are unknown, which is a challenging difficulty in image blind de-blurring. According to the method, on the basis of image block posteriori, a multi-scale non-local regularization strategy is introduced. The strategy is added on the two most rough layers of image pyramid calculation blurring kernels, the understanding space range is limited effectively, and accordingly, the blurring kernel calculation is evolved towards the accurate direction, clear blurring kernels are calculated, the basis is laid for the next step of sharp image calculation, image blind de-blurring is achieved through an image non blind de-blurring method, and the experiment result shows that the method is more effective and better than some existing advance methods.

Description

technical field [0001] The invention belongs to the technical field of natural image processing, and relates to the application of blind deblurring of images, in detail, it is a blur kernel estimation method using multi-scale non-local regularization. Using this method can estimate the cause of image blur more effectively, so as to further obtain a clear posterior image. It has a wide range of applications and can restore blurred images for many different blur types. Background technique [0002] Blind image deblurring refers to estimating the degradation reasons of some blurred images that have been obtained, that is, to find out the blur kernel, and then restore the image, because the clear posterior image and the blur kernel are unknown, which makes blind deblurring Ambiguity has become a deeply morbid problem. This technology is also widely used in real life. For example, in the process of our video recording or taking pictures, due to the defocus of the imaging device,...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 王爽焦李成蔺少鹏岳波刘红英熊涛马晶晶罗萌
Owner XIDIAN UNIV
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