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Method and device for realizing Gaussian blur

A technology of Gaussian blur and implementation method, applied in the field of image processing, can solve the problem of unacceptable efficiency, and achieve the effect of reducing the amount of calculation and improving the processing speed

Inactive Publication Date: 2010-06-30
CHINA DIGITAL VIDEO BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Furthermore, Gaussian blur cannot use some optimization methods of box blur for processing optimization. Therefore, for high-efficiency image / video processing software, the efficiency of the Gaussian blur method provided in the prior art is often unacceptable

Method used

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  • Method and device for realizing Gaussian blur

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Experimental program
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Embodiment 1

[0039] Such as figure 1 As shown, a Gaussian blur implementation method includes the following steps:

[0040] (1) Determine the convolution kernel width K according to the image processing width width input by the user, specifically:

[0041] First, determine the convolution kernel radius R according to R=ceil(3*width);

[0042] Then, the convolution kernel width K is determined according to K=2*R+1.

[0043] (2) Determine the specific value of the convolution kernel according to the convolution kernel width K and the Gaussian function.

[0044] (3) Perform two one-dimensional Gaussian convolutions on the image to be processed according to the determined convolution kernel to obtain the target image. The steps are specifically:

[0045] First, perform horizontal one-dimensional Gaussian convolution on each row of the image to be processed from the horizontal direction;

[0046] Then, perform vertical one-dimensional Gaussian convolution on the result of the above-mention...

Embodiment 2

[0056] The difference between this embodiment 2 and embodiment 1 is that, on the basis of embodiment 1, this embodiment 2 fully considers when performing horizontal one-dimensional Gaussian convolution, in order to solve the problem of pixel values ​​in the neighborhood adjacent to the boundary pixel problem, and the introduction of a large number of conditional branch statements, thus affecting the computational efficiency of the problem. Because, when performing horizontal one-dimensional Gaussian convolution, it is calculated by multiplying and summing the pixel value in each pixel neighborhood (that is, the neighborhood with a width of K) and the one-dimensional Gaussian convolution kernel, However, for some pixels that are closer to the image boundary, the pixels in the neighborhood have exceeded the starting position or the ending position of the line. Usually, it is necessary to use the method of boundary pixel extension to simulate these pixels, that is, if it is less t...

Embodiment 3

[0060] The difference between this embodiment 3 and embodiment 1 is that, on the basis of embodiment 1, this embodiment 3 fully considers that after performing horizontal one-dimensional Gaussian convolution, a larger buffer is required for data storage, so as to Causes the problem of lower CPU cache utilization. Because in the implementation method of Gaussian blur introduced in Example 1, since the horizontal one-dimensional Gaussian convolution is performed on the image first, and then the vertical one-dimensional Gaussian convolution is performed, it is usually necessary to allocate a buffer as large as the original image area to store the result of horizontal one-dimensional Gaussian convolution, and then use the image in this buffer (that is: the result of horizontal one-dimensional Gaussian convolution) as input to perform vertical one-dimensional Gaussian convolution, and put the result into the target image. Therefore, when the image size is relatively large, it is ne...

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Abstract

The invention relates to a method and a device for realizing Gaussian blur, belonging to the technical field of image processing. The prior art has the defects that the calculated amount for realizing Gaussian blur is large and the processing speed is slow. The method of the invention comprises that horizontal one-dimensional Gaussian convolutions and vertical one-dimensional Gaussian convolutions are sequentially conducted to images to be processed. The invention additionally discloses a device for realizing the method. The device comprises an external input receiving unit, a convolution kernel generation unit, a horizontal convolution unit and a vertical convolution unit, wherein the external input receiving unit is used to determine the width of a convolution kernel according to the processing width of the received images, the convolution kernel generation unit is used to determine the specific values of the convolution kernel according to the width of the convolution kernel and the Gaussian function, the horizontal convolution unit is used to conduct horizontal one-dimensional Gaussian convolutions to each line of the images to be processed, and the vertical convolution unit is used to vertical one-dimensional Gaussian convolutions to the results of the horizontal one-dimensional Gaussian convolutions. By adopting the method and the device of the invention, the calculated amount for realizing Gaussian blur is reduced and the processing speed is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method and device for realizing Gaussian blur. Background technique [0002] In image / video processing software, blurring image / video content is a very wide demand. At present, there are usually two methods for blurring, one is box blur (boxblur), and the other is Gaussian blur (Gaussian blur), where: [0003] Box blur is a simple and fast blur processing method, but its blur effect is not good, especially when the blur degree is relatively large; [0004] Gaussian blur is considered to be the most ideal blur processing method at present. Its blur effect looks very natural and comfortable, but the calculation amount of Gaussian blur is usually much larger than that of box blur. Specifically, in image processing In the process, Gaussian blur is the result of convolving an image with a two-dimensional Gaussian function. The Gaussian function is defined as ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 见良郑鹏程刘铁华孙季川
Owner CHINA DIGITAL VIDEO BEIJING
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