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Image sharpening method based on non-causal fractional order subdifferential

A fractional order, image sharpening technology, applied in the field of image processing, to achieve the effect of keeping the phase characteristics unchanged, reducing noise, and strong noise suppression ability

Active Publication Date: 2016-08-17
ANHUI UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0007] Aiming at the difficult problem of how to achieve a compromise between enhancing image details and resisting noise in the process of image sharpening, the present invention provides an image sharpening method based on non-causal fractional order differentiation; the present invention is based on non-causal The novel algorithm of fractional order differentiation performs differential operations, which can effectively suppress noise while enhancing image detail information, and can greatly enhance image details while suppressing the influence of noise. Subdifferential Image Sharpening Method A More Ideal Sharpening Algorithm

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  • Image sharpening method based on non-causal fractional order subdifferential

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Embodiment 1

[0061] see figure 1 , this embodiment mainly implements non-causal fractional order differentiation in the X direction and Y direction to obtain a sharpened image, and the specific steps are:

[0062] (1) Read an image f(x,y) to be sharpened;

[0063] (2) Carry out α-order causal differential filtering and anti-causal differential filtering for each pixel point along the X direction; among them, the causal fractional order differential is realized by mask convolution, and the causal mask in the X direction is as follows:

[0064] x causal =[a m …a k …a 1 a 0 0...0...0]

[0065] The anti-causal fractional order differentiation is realized by mask convolution, and the anti-causal mask in the X direction is as follows:

[0066] x anticausal =[0...0...0a 0 a 1 …a k …a m ]

[0067] In the above formula,

[0068] a k = ( - 1 ) k ...

Embodiment 2

[0087] see figure 2 , an image sharpening method based on non-causal fractional order differentiation in this embodiment is basically the same as in embodiment 1, the difference is that: this embodiment performs non-causal fractional order differential filtering in the X direction and the Y direction On the basis of , the non-causal fractional order differential filtering is further carried out in the two diagonal directions, that is, the causal fractional order differential image g in the Y direction is obtained 2 After (x,y), for g 2 (x, y) Each pixel point along the 45° direction performs μ-order causal differential filtering and anti-causal differential filtering respectively;

[0088] 45° direction differential mask (X 45° Middle 45° means rotate X by 45°).

[0089] Add the μ-order causal differential and anti-causal differential results in the 45° direction to get the non-causal fractional differential image g 3 (x,y); then add the result g 3 (x, y) Each point al...

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Abstract

The invention discloses an image sharpening method based on non-causal fractional order subdifferential and belongs to the technical field of image processing. Non-causal fractional order subdifferential is performed on to-be-sharpened images by combining causal fractional order subdifferential with anti-causal fractional order subdifferential, the final amplitude frequency gain is adjusted by adjusting the value of differential order, resistance to noise and sensitivity to image detail information are further adjusted, then final non-causal fractional order subdifferential images are added to original to-be-sharpened images in a certain form, and final sharpened images are obtained. Differential operation is performed on the basis of the novel algorithm of non-causal fractional order subdifferential, noise can be effectively inhibited while the image detail information is enhanced, image details can be enhanced greatly while the effect of noise is inhibited, and the method can be widely applied to fields of image analysis, automatic target recognition and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an image sharpening method, in particular to an image sharpening method based on non-causal fractional order differentiation. Background technique [0002] The main purpose of image sharpening is to highlight details in an image or enhance blurred details. Image smoothing often blurs the boundaries and outlines in the image. In order to reduce the impact of such adverse effects, it is necessary to use image sharpening technology to make the edges, contour lines and details of the image clear. The root cause of the blurred image is that the image is subjected to averaging or integral operations. Therefore, by performing differential operations on the image, the image can be made clear and the purpose of image sharpening can be achieved. [0003] The sharpening method based on the traditional integer-order differential is a widely used image sharpening technique, such as th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20024G06T5/73
Inventor 潘祥吴媛媛姜太平李伟边琼芳邰伟鹏刘恒
Owner ANHUI UNIVERSITY OF TECHNOLOGY
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