Impulse noise blurred image nonlinear restoration method and system

A technique for impulsive noise and blurred images, which is applied in the field of nonlinear restoration methods and systems for pulse noise blurred images, and can solve the problems of poor quality of restored images, sensitivity, and errors in restoration results.

Active Publication Date: 2020-02-28
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0011] The image deblurring method based on traditional linear data items is sensitive to noise. When the image is degraded by impulse noise, the restored image has serious ringing phenomenon, cannot restore a clear image, and the quality of the restored image is poor.
[0012] In the first category of methods for the restoration of noisy nonlinear degraded blurred images, the setting of the heuristic detection step is usually without theoretical guidance. When the heuristic detection step is inaccurate, there may be a large restoration error in the restoration result
[0013] The second type of method has a better theoretical explanation, but when the selected non-L2 norm data items are not accurate in modeling the nonlinear degradation factors or the constraints are not strong enough, there will be large errors in the restoration results

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  • Impulse noise blurred image nonlinear restoration method and system

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Embodiment 1

[0161] For blurred images with salt and pepper noise (a kind of impulse noise), the deblurring solution is as follows:

[0162] (1) For the salt and pepper noise fuzzy image, establish its degradation mechanism model, and then determine the optimization model: The nonlinear degradation model of the fuzzy image with salt and pepper noise is shown in (1):

[0163]

[0164] : Among them, x is the original clear image, K is the known blur kernel, Is a fuzzy image not polluted by noise, H sp Represents the process in which the image is further contaminated by salt and pepper noise, and y is the final degraded image.

[0165] According to the degradation model (1), the following optimization models are determined:

[0166]

[0167] Where Ψ(Kx-y) is the data item, It is the image prior term (ie, regularization term).

[0168] (2) According to the optimization model obtained in step (1), construct data items to model impulse noise:

[0169] For the deconvolution model constructed based on the...

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Abstract

The invention belongs to the technical field of digital image processing, and discloses an impulse noise blurred image nonlinear restoration method and system, and the method specifically comprises the steps: building an impulse noise blurred image degradation mechanism model, and determining an optimization framework; constructing data items to model impulse noise; selecting an image prior item,and constructing a pulse noise blurred image non-blind deconvolution model in combination with the data item; and performing numerical optimization solution on the non-blind deconvolution model by using an iterative reweighted least square algorithm and a conjugate gradient method to obtain a restored image. According to the impulse noise blurred image nonlinear restoration method, properties of impulse noise are analyzed, a nonlinear deconvolution model is designed in a targeted mode, and the nonlinear degenerated impulse noise blurred image restoration problem is solved.

Description

Technical field [0001] The present invention belongs to the technical field of digital image processing, and particularly relates to a method and system for non-linear restoration of impulse noise blurred images. Background technique [0002] At present, the existing technology commonly used in the industry is as follows: [0003] When the image is degraded by noise and blur, the quality of the image is seriously degraded. On the one hand, the visual effect of the image is reduced. On the other hand, the degradation interferes with the high-level tasks of the image, such as segmentation, target detection and recognition, etc., which seriously weakens the image. Use value. Therefore, restoration of degraded images is very necessary. The problem of image deblurring is a classic image restoration problem. Non-blind deconvolution is a key part of many deblurring algorithms. Non-blind refers to the known blur kernel in the image degradation process. The non-blind deblurring algorithm...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/003G06T2207/20201
Inventor 颜露新曹舒宁陈妹雅昌毅李祎李子沁叶云桐
Owner HUAZHONG UNIV OF SCI & TECH
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