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A Total Variational Image Denoising Method Based on Noise Prior Constraints

A total variation and image technology, applied in the field of full variation image denoising, can solve the problems of image pollution, image ladder effect, unsatisfactory suppression effect, etc., and achieve good denoising performance

Active Publication Date: 2019-11-15
TIANJIN UNIV
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Problems solved by technology

At present, most of the existing improvement methods consider removing the noise of Gaussian distribution, but the noise in some cases does not always obey the Gaussian distribution. For example, impulse noise will be generated during the transmission and storage of the imaging process. noise pollution
The full variational denoising model has problems such as misjudging the image noise as an edge, resulting in false edges and making the restored image in the smooth gradient area present a staircase effect.
At present, the suppression effect of the traditional single denoising method for mixed noise is not ideal, so the algorithm for suppressing mixed noise is a combination of multiple denoising algorithms

Method used

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  • A Total Variational Image Denoising Method Based on Noise Prior Constraints
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  • A Total Variational Image Denoising Method Based on Noise Prior Constraints

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Embodiment Construction

[0041] The present invention adopts following technical scheme:

[0042] The full variational image denoising method based on noise prior constraints is carried out according to the following steps:

[0043]Step 1): Input a noise-containing image I, the size is m×n, the gray level is between 0 and H, and H is usually 255, but normalization is performed in the image processing, and the image pixel value is between 0 and 1 ;

[0044] Step 2) let f be the original clear image, u be the noise observation image of f, and the noise model is set up as u=f+N, wherein, N represents the Gaussian random white noise whose mean value is zero and variance is σ;

[0045] Step 3): Image u is further affected by impulse noise during transmission and storage, and g represents an image contaminated by mixed noise, and i represents each pixel, and the value of each pixel in the image is represented by a nonlinear model, which is

[0046] Among them, v i Represents the pixel value polluted b...

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Abstract

The present invention belongs to the technical field of digital image processing. In order to propose a total variation image denoising method based on noise prior constraints, which can improve the accuracy of noise detection and well protect image structure information; the present invention adopts the following technical solutions : Total variational image denoising method based on noise prior constraints, follow the following steps: Step 1) Input the noisy image I; Step 2) Let f be the original clear image; Step 3) Image u is transmitted and During the storage process, the image is further affected by impulse noise, and g is used to represent the image contaminated by mixed noise. Step 4) Use the ROAD statistical method to estimate the position of the noise point; Step 5) Construct a TV‑ROAD iterative denoising model; Step 6) Based on the results obtained in the previous step To denoise the image f, obtain the binary matrix vector b by solving the following formula I . The present invention is mainly used in digital image processing.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a full variational image denoising method based on noise prior constraints, which can be used in the fields of medicine, industry and agriculture, astronomy and the like. Background technique [0002] During the process of acquiring, transmitting and recording image signals, they are often disturbed by various noises, which seriously affect the visual effect of images. With the popularization of various digital instruments and digital products, images and videos have become the most commonly used information carriers in human activities. They contain a lot of information about objects and become the main way for people to obtain original information from the outside world. Therefore, adopting appropriate methods to reduce noise is an important branch in the research of digital image processing. Traditional spatial domain filters and frequency domain ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/70
Inventor 冀中赵硕刘立
Owner TIANJIN UNIV
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