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Fractional order I-divergence method for improving visual effect of images

A fractional, image technology, applied in the field of fractional I-divergence to improve the visual effect of the image, can solve the problem of missing detail information, and achieve the goal of suppressing multiplicative noise, balancing edge protection ability and fidelity, and improving the visual effect of the image. Effect

Inactive Publication Date: 2015-04-22
SHENYANG UNIV
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However, the models are all built in the bounded variation space, and the function of this space has the characteristic of piecewise smoothness, so there is an obvious "step effect" in the steady-state solution, that is, some detailed information is lost, and the phenomenon of piecewise smoothing occurs

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  • Fractional order I-divergence method for improving visual effect of images

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Embodiment Construction

[0035] Below in conjunction with embodiment, the present invention is described in further detail.

[0036] First construct a fractional gradient operator, for a finite-dimensional vector space Any 2D image in , assuming an image size of M x N , then its fractional differential discrete form is defined as:

[0037] (9)

[0038] In the formula,

[0039] (10)

[0040] In the formula, is an integer constant, , Represents the Gamma function.

[0041] It can be seen that the fractional order differential is global. Compared with the traditional first-order differential, it can consider more image neighborhood information, protect more image detail features, and alleviate the "staircase effect" phenomenon.

[0042] Accordingly, the present invention makes fractional expansion based on the I-divergence model, and proposes a fractional I-divergence denoising model,

[0043] (11)

[0044] In the formula,

[0045] (12)

[0046] Regularization parameters in...

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Abstract

A fractional order I-divergence method for improving the visual effect of images relates to a computerized realization method for removing multiplicative noise of images. The method comprises a fractional order I-divergence de-noising model, a regularization parameter adjustment method, and a fractional order I-divergence primal-dual numerical algorithm. The method is characterized in that the expression of the fractional order I-divergence de-noising model is shown in the specification. The resolvent fractional order primal-dual numerical algorithm is adopted in numerical calculation of the model, and the defect that certain traditional numerical algorithms have extremely high requirement on the step size is overcome through self-adaption variable-step-size iteration of the algorithm. Experimental results show that the fractional order I-divergence de-noising method provided by the invention can effectively improve the visual effect of images and inhibit the 'staircase effect', and can be quickly realized in a computerized way.

Description

technical field [0001] The invention relates to a computer-implemented method for image multiplicative noise removal, in particular to a fractional I-divergence method for improving image visual effects. Background technique [0002] Image denoising is an inverse problem of finding the original clear image from the noisy image. It has a fundamental position in the field of digital image processing and plays a preprocessing role in subsequent image restoration, image segmentation, image registration and other processing processes. According to the correlation between image and noise, image noise can be divided into additive noise and multiplicative noise. In the image denoising problem, most of the current researches focus on additive noise. In practical applications, multiplicative noise commonly exists in synthetic aperture radar images, medical images, microscopic images, and laser images. Therefore, the research on image multiplicative noise removal has wide applicatio...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 田丹王丹
Owner SHENYANG UNIV
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