Non-local mean space domain time varying image filtering method

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...

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