Video denoising system based on noise correlation

Patent metadata

Field	Value
Publication number	US-10242432-B2
Application number	US-201515557085-A
Country	US
Kind code	B2
Filing date	Apr 16, 2015
Priority date	Apr 16, 2015
Publication date	Mar 26, 2019
Grant date	Mar 26, 2019

Abstract

The present invention discloses a video denoising system based on noise correlation, said system comprises a unit for estimating correlation of noises of adjacent pixels, which receives input of the inter-frame difference and motion probability, and estimates correlation of noises of adjacent pixels according to correlation of inter-frame differences between adjacent pixels in a still region, and outputs a noise correlation coefficient; a maximum filtering weight adjusting unit, which adaptively adjusts the maximum weight for temporal filtering according to the noise correlation coefficient and outputs the maximum weight for temporal filtering; the maximum weight for temporal filtering can control the range of fluctuation of the temporal filtering weight and the difference between the denoising effects for different pixels. The system of the present invention can solve the problem of “speckle” noise occurred when the video noises have adjacent correlation in the conventional temporal denoising system for videos.

First claim

What is claimed is:

1. A video denoising system based on noise correlation, which comprises: a frame memory, an inter-frame difference calculating unit, a motion detection unit, a filtering weight calculating unit, and a temporal filtering unit, characterized in that said system further comprises a unit for estimating correlation of noises of adjacent pixels, and a maximum filtering weight adjusting unit;
the unit for estimating correlation of noises of adjacent pixels calculates a noise correlation coefficient r h of horizontally adjacent pixels, a noise correlation coefficient r v of vertically adjacent pixels, a noise correlation coefficient r d of diagonally adjacent pixels according to an inter-frame difference d output from the inter-frame difference calculating unit and a motion probability m of each pixel output from the motion detection unit, and outputs the maximum value of r h , r v and r d as a noise correlation coefficient r;
the maximum filtering weight adjusting unit calculates and outputs a maximum weight Mw for performing temporal filtering according to the noise correlation coefficient r;
the filtering weight calculating unit calculates and outputs a filtering weight w for performing temporal filtering according to the motion probability m of each pixel and the maximum weight Mw for filtering.

2. The video denoising system based on noise correlation as claimed in claim 1 , characterized in that the unit for estimating correlation of noises of adjacent pixels calculates a noise correlation coefficient r by the equation of:
wherein c h , c v , c d are combination coefficients, r h is noise correlation coefficient of horizontally adjacent pixels, r v is a noise correlation coefficient of vertically adjacent pixels, r d is a noise correlation coefficient of diagonally adjacent pixels.

3. The video denoising system based on noise correlation as claimed in claim 1 , characterized in that the unit for estimating correlation of noises of adjacent pixels calculates a noise correlation coefficient r by the equation of:
r =max( r h ,r v ,r d )
wherein r h is a noise correlation coefficient of horizontally adjacent pixels, r v is a noise correlation coefficient of vertically adjacent pixels, r d is a noise correlation coefficient of diagonally adjacent pixels.

4. The video denoising system based on noise correlation as claimed in claim 1 , characterized in that the correlation coefficient r h of horizontally adjacent pixels, the correlation coefficient r v of vertically adjacent pixels, the correlation coefficient r d of diagonally adjacent pixels are calculated by the following equations:

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Assignees

• Inst Automation Cas

Inventors

• Guo Ruoshan
• Ye Lu
• Han Rui
• Luo Yang
• Tang Renjun
• Yan Fengli
• Tang Xiaoli

Classifications

• G06T5/002 Primary

  Physics · mapped topic

• H04N5/21

  Circuitry for suppressing or minimising disturbance, e.g. moiré or halo · CPC title

• G06T2207/20208

  High dynamic range [HDR] image processing · CPC title

• G06T5/20

  using local operators · CPC title

• G06T2207/20182

  Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering · CPC title