Video denoising method based on scale mixing model and low-rank approximation

A hybrid model and video technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as lack of consideration of the correlation between before and after frames, video blurring, and affecting video processing.

Inactive Publication Date: 2016-11-23
西安电子科技大学昆山创新研究院 +1
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Problems solved by technology

[0008] These two types of methods lack the consideration of the correlation between the front and back frames, and do not fully utilize the existing information in

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  • Video denoising method based on scale mixing model and low-rank approximation
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  • Video denoising method based on scale mixing model and low-rank approximation

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Embodiment Construction

[0040] Referring to the accompanying drawings, the technical solutions and effects of the present invention are described in detail below:

[0041] refer to figure 1 , the implementation steps of the present invention are as follows:

[0042] Step 1. Perform median filter preprocessing on the input noisy video sequence y to obtain the initial estimated video y 0 .

[0043] (1a) For noisy video y={y 1 ,...,y t ,...,y T}∈R M×N×T Noisy image y in the tth frame t ∈ R M×N The i-th pixel in Perform a median filter, that is, to Take an image block x of size n as the center i,t , take image block x i,t The median value of internal pixels is Me, if The absolute value of is greater than or equal to the preset threshold τ, it is considered that the pixel Impulse noise, its pixel value after median filtering Otherwise, consider the pixel Not affected by impulse noise, the pixel value remains unchanged after median filtering, where t∈{1,2,...,T}, T represents the numbe...

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Abstract

The invention discloses a video denoising method based on a scale mixture model and a low-rank approximation, which mainly solves the problem that it is difficult to accurately remove Gaussian pulse mixture noise in the prior art. The scheme is: 1. Use the median filter method to obtain the initial estimate of the video, and find similar image block matrices in the front and rear frames of the test image; 2. Use the Laplacian scale mixture model to model the abnormal point set, and the abnormal points The problem of point estimation is transformed into a joint solution of outliers and hidden factors to remove outliers caused by mixed noise; 3. Perform low-rank approximation to similar image block matrices, and use non-local low-rank models to calculate denoised images; 4 .Use the Laplacian scale mixture model and the non-local low-rank model to iteratively calculate the restored single-frame image; 5. Repeat 1‐4 to obtain the denoised video. The invention can remove mixed noise, retain image detail information, have better visual effect, and can be used for denoising video multimedia, remote sensing images and medical images.

Description

technical field [0001] The invention relates to the field of video denoising, in particular to a video denoising method based on a scale mixture model and low-rank approximation, which can be applied to the fields of video multimedia, remote sensing images, medical images, and the like. Background technique [0002] Video sequences will inevitably receive noise interference during storage and transmission, which will be directly related to subsequent video processing applications, such as target tracking, target recognition, video compression, etc. Therefore, in video processing, video denoising plays an important role. very important role. The video acquisition process will introduce Gaussian noise, while dead pixels or transmission errors in the camera equipment will introduce impulse noise. Impulse noise can be divided into salt and pepper noise and random value noise. The pixel value affected by salt and pepper noise is 0 or 255, while the pixel value affected by random...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/003G06T5/002G06T2207/10016G06T2207/20032
Inventor 董伟生石光明黄韬
Owner 西安电子科技大学昆山创新研究院
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