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Video noise estimation method based on main component analysis

A principal component analysis, video noise technology, applied in the field of video noise estimation, can solve problems such as unsatisfactory denoising effect, inaccurate noise parameters, dependence on noise-containing video noise parameters, etc., achieving small errors, accurate estimation results, and wide adaptability Effect

Active Publication Date: 2017-10-24
ZHONGYUAN WISDOM CITY DESIGN RES INST CO LTD
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AI Technical Summary

Problems solved by technology

The performance of most existing video denoising algorithms depends to varying degrees on the noise parameters in the noisy video
Although various algorithms can achieve ideal denoising effects, most algorithms have an assumption that the noise intensity is known in advance.
Artificially given noise parameters or inaccurate noise parameters will lead to unsatisfactory denoising effect

Method used

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  • Video noise estimation method based on main component analysis
  • Video noise estimation method based on main component analysis
  • Video noise estimation method based on main component analysis

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Embodiment Construction

[0018] The technical solutions of the present invention will be described in further detail below through specific implementation methods.

[0019] Such as figure 1 As shown, a video noise estimation method based on principal component analysis, including the following steps:

[0020] Step 1, input a noisy video frame, perform block matching on the current frame image and the next frame image, and calculate the difference image blocks of each pair of corresponding sub-blocks in the current frame image and the next frame image, and select the best matching effect A pair of differential image blocks corresponding to the sub-blocks are used as the original noisy image;

[0021] Specifically, the two frames before and after the video image sequence have a strong correlation in time. For a block that originally has a lot of texture and detail information, if it has a strong correlation between the two frames before and after, then the result of the difference still produces a smo...

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Abstract

The invention provides a video noise estimation method based on main component analysis. Video sequence correlation is fully used, and similar block searching is carried out between adjacent frames of images, and based on a minimum cost criterion, a differential image between the adjacent frames of images is acquired, and influences of video motion are eliminated, and then a preliminary weak texture difference image is acquired. Noise estimation based on video blocks is introduced, and noise level parameters are acquired in a self-adapting way, and a normal distribution function is adopted as a threshold function of selection of a weak texture block, and then calculation complexity is reduced. The estimated noise level is more accurate by adopting a clear iteration index, and then an underestimation phenomenon under a condition of a high noise level is prevented. The video noise estimation method can be used in a blind video denoising filed, and has advantages of accurate estimation and wide application prospect.

Description

technical field [0001] The invention relates to a method for estimating video noise, in particular to a method for estimating video noise based on principal component analysis. Background technique [0002] Noise can be introduced into video signals during capture, recording and transmission. The introduced noise seriously reduces the video picture quality and affects the audience's visual experience. Video denoising is a multimedia information processing technology that combines the characteristics of digital video images with existing signal processing technologies to reduce noise interference in video images as much as possible. The performance of most existing video denoising algorithms depends to varying degrees on the noise parameters in noisy videos. Although ideal denoising effects can be achieved through various algorithms, most algorithms have an assumption that the noise intensity is known in advance. Artificially given noise parameters or inaccurate noise para...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/21
CPCH04N5/21
Inventor 陈长宝杜红民侯长生孔晓阳王茹川郭振强郧刚王磊王莹莹肖进胜
Owner ZHONGYUAN WISDOM CITY DESIGN RES INST CO LTD
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