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Non-local mean space domain time varying image filtering method

A non-local mean and image filtering technology, applied in the field of image processing, which can solve the problems of long calculation time and restricting the application of non-local mean filter.

Inactive Publication Date: 2010-06-16
XIDIAN UNIV
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Problems solved by technology

This huge computational complexity causes the calculation time to be too long, which greatly limits the application of non-local mean filter. For example, the non-local mean filter method of this computational complexity cannot be applied in real-time embedded systems.

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  • Non-local mean space domain time varying image filtering method

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Embodiment Construction

[0068] see figure 2 , a kind of non-local mean spatial domain time-varying image filtering method that technical scheme 1 of the present invention proposes, comprises the following steps:

[0069] Step 1: Obtain original image information, set filtering parameters, and initialize non-normalized filtered image I(x, y) and weight normalization coefficient α(x, y).

[0070] The filter-related parameters set include search domain shape, matching window size, weighted kernel width h and similarity comparison norm parameter p; the search domain is a rectangle, triangle, circle or any polygon, and the matching window shape is a rectangle, set in The weighted kernel width h and the similarity comparison norm parameter p when calculating the weighted kernel weight according to the image bias similarity function value; the weighted kernel width h is any positive real number, and the similarity comparison norm parameter p is any non-negative real number ; The value I(x, y) and the weig...

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Abstract

The invention discloses a non-local mean space domain time varying image filtering method, mainly solving the problem that the existing non-local mean space domain time varying filter is large in computation amount and restricted in application range. The filtering process includes that: weight normalization coefficient and value after non-normalization filtering at all the points of the original image are initialized to be zero; for polarization of each coordinate in search domain, all the pixel points of the original image are subject to uniform pre-treatment, then a weighting verifying value of all the pixel points of the original image at the coordinate in the search domain is rapidly calculated; the weight normalization coefficient and the value after non-normalization filtering are updated according to the weighting verifying value; and the image after filtering is obtained by calculation according to the weight normalization coefficient and the value after non-normalization filtering. The invention greatly reduces the computational complexity of the existing non-local mean space domain time varying filtering method and can be applicable to the image restoring, image de-noising and image super resolution rebuilding fields.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to an image filtering method, in particular to a time-varying image filtering method in non-local mean value space, which is used for processing digital images and video images. technical background [0002] With the development of information and multimedia technology, the application of digital image processing technology is more and more extensive. Spatial filtering technology is one of the basic methods of digital image processing, and has a wide range of applications in the field of digital images, such as image restoration, image denoising, image super-resolution reconstruction, etc. The basic idea of ​​spatial filtering is to use the relationship between adjacent pixels to obtain the corresponding processing purpose. The shape composed of adjacent pixels is called the search domain. For any pixel in the image, the filtered value of this point is equal to the normalized weighte...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/10
Inventor 齐飞付莹石光明韩钧宇张犁吴家骥
Owner XIDIAN UNIV
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