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Image noise estimating method, video image de-noising method, image noise estimating device, and video image de-noising device

A noise estimation and image technology, applied in the field of image processing, can solve the problem of inaccurate image noise estimation

Active Publication Date: 2015-06-03
ZHEJIANG DAHUA TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Embodiments of the present invention provide an image noise estimation method, a video image denoising method and device, to solve the problem of inaccurate image noise estimation in the prior art

Method used

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  • Image noise estimating method, video image de-noising method, image noise estimating device, and video image de-noising device
  • Image noise estimating method, video image de-noising method, image noise estimating device, and video image de-noising device
  • Image noise estimating method, video image de-noising method, image noise estimating device, and video image de-noising device

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Embodiment 1

[0061] In Embodiment 1 of the present invention, an image noise estimation method is provided, such as image 3 As shown, it specifically includes the following steps:

[0062] S301. Determine the Laplacian operators in two directions of the image to be processed, wherein the Laplacian operators in the two directions meet the following conditions: preset the Laplacian operators in the two directions In the difference operator obtained by linear operation, the sum of the values ​​in each row and the sum of the values ​​in each column are both zero, and the absolute value of the value at the center is greater than the absolute value of the value at the non-center position.

[0063] Further, assuming that the determined Laplacian operators in two directions of the image to be processed perform the linear operation as in formula (1), the difference operator dL is obtained:

[0064] dL=aL 1 -bL 2 ; (1)

[0065] Among them, L 1 and L 2 respectively represent the Laplacian op...

Embodiment 2

[0080] In Embodiment 2 of the present invention, a video image denoising method is provided, such as Figure 5 As shown, it specifically includes the following steps:

[0081] S501. Determine the noise variance of the current frame image of the video to be processed based on the above image noise estimation method, and determine a motion detection threshold according to the noise variance.

[0082] Further, a preset coefficient may be used to multiply the noise variance according to actual needs, and the product may be determined as the motion detection threshold.

[0083] Further, there is no strict execution sequence between this step and steps S502-S503, that is, as long as the motion detection threshold is determined before step S504.

[0084] S502. Based on the second preset size, respectively divide the current frame image and the previous frame image into non-overlapping blocks to obtain each image block of the current frame image and each image block of the previous f...

Embodiment 3

[0097] In Embodiment 3 of the present invention, a video image denoising method is provided, such as Figure 6 As shown, it specifically includes the following steps:

[0098] S601. Determine the noise variance of the current frame image of the video to be processed based on the above image noise estimation method, and determine a motion detection threshold according to the noise variance.

[0099] Further, there is no strict execution sequence between this step and steps S602-S604, that is, as long as the motion detection threshold is determined before step S605.

[0100] S602. Based on the second preset size, respectively divide the current frame image and the previous frame image into non-overlapping blocks to obtain each image block of the current frame image and each image block of the previous frame image.

[0101] S603. For each image block of the current frame image and the previous frame image, determine an image area composed of s×s image blocks centered on the imag...

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Abstract

The embodiment of the invention provides an image noise estimating method, a video image de-noising method, an image noise estimating device, and a video image de-noising device. The image noise estimating method comprises the following steps: determining the Laplasse operators of an image to be processed in two directions, wherein, among difference operators obtained through default linear operation on the Laplasse operators in two directions, the sum of numerical values in all rows and the sum of numerical values in all columns are zero, and the absolute value of the numerical value in the center is larger than the absolute value of a numerical value not in the center; smoothing the image to be processed by use of the difference operators to obtain a smooth image; partitioning the smooth image in a non-overlapping way based on a first preset size to obtain image blocks; and determining the variance of each image block, determining a preset number of variances according to the order of the variances from small to large, and determining the weighted average of the preset number of variances as an estimated noise variance of the image to be processed. The problem that image noise estimation is inaccurate in the prior art is solved. The invention relates to the field of image processing.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image noise estimation method, a video image denoising method and a device. Background technique [0002] During the transmission of images or videos, they will be polluted by various noises, which will cause the resolution of the images or videos received by the receiver to be reduced compared with the original images or videos, which not only affects the visual effect, but also affects the image or video that needs to be obtained or recognized. Images or videos of moving targets affect the accuracy of acquisition or recognition. Therefore, in the prior art, it is necessary to estimate noise in an image or a video frame image, so as to prepare for subsequent denoising processing. [0003] In the prior art, methods for estimating noise in images or video frame images mainly include the following steps: [0004] Step 1, performing non-overlapping block processing on the image ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/00
Inventor 郭一民叶昕刘敏潘石柱张兴明
Owner ZHEJIANG DAHUA TECH CO LTD
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