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Real-time blind image restoration method

A real-time image, blind restoration technology, applied in the field of image processing, can solve problems such as poor real-time performance and inaccurate point spread function estimation, and achieve the effect of avoiding estimation distortion

Inactive Publication Date: 2015-08-05
XI AN JIAOTONG UNIV +1
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: in order to overcome the disadvantages of the poor real-time performance of the iterative blind restoration method in the application of image restoration technology, and the inaccurate estimation of the point spread function by the non-iterative blind restoration method, the present invention proposes a method based on image spectrum and frequency logarithm Image Blind Restoration Method for Relation

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Embodiment Construction

[0046] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] like figure 1 As shown, the real-time image blind restoration method of the present invention comprises the following steps:

[0048] 1) Perform Fourier transform on the degraded image g(x) to obtain a blurred image G(μ, v),

[0049] Take σ=G(0,0), and normalize G(μ,v), get

[0050] G * (μ, v) = G(μ, v) / σ (1)

[0051] Among them, G * (μ, v) is the normalized frequency of the degraded image, G(μ, v) is the blurred image, σ is the normalization constant, take σ=F(0,0)≈G(0,0), that is, the degradation The value of the Fourier transform of the image at the origin.

[0052] 2) According to the spectrum distribution law of natural images, the spectrum of the original image of the degraded image is reconstructed, and the reconstruction formula of the original image spectrum (taking μ=0 as an example) is

[0053] ln | ...

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Abstract

The invention provides a real-time blind image restoration method, which comprises the following steps of carrying out Fourier transformation on a degraded image, and then obtaining a normalized spatial spectrum of the degraded image; reconstructing a frequency spectrum of an original image of the degraded image according to a spectral distribution rule of a natural image and estimating a normalized spatial spectrum of the original image; comparing the normalized spatial spectrum of the degraded image and a reconstructed frequency spectrum, and obtaining an optical transfer function of a system so as to obtain a point spread function of the degraded image; and carrying out Wiener filtering restoration on the degraded image according to the obtained point spread function so as to obtain an ideal image. The real-time blind image restoration method does not contain time-consuming iteration, and is simple and easy to implement, so that algorithm complexity is reduced, meanwhile, accurate estimation of the point spread function is obtained, and a good image restoration effect is realized.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to the theory and method of adaptive optics image restoration, in particular to a real-time fast image blind restoration algorithm in adaptive optics. Background technique [0002] Image restoration is based on the cause of image degradation, using the observed degraded images to restore a clear real scene. Image restoration technology has been widely used in many fields such as astronomical observation, remote sensing, security monitoring and medical imaging. In most cases, the PSF (Point Spread Function) of image degradation is unknown, so the restoration process for degraded images usually uses a blind restoration algorithm. At present, most blind restoration algorithms are iterative in nature. Due to some pathological problems of degraded image data, local convergence or divergence often occurs in the iterative blind restoration process; even if the iterative process is ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 邹建华高伟哲赵玺张志广王斌
Owner XI AN JIAOTONG UNIV
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