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TV (total variation) image noise removal method based on noise priori constraint

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

Active Publication Date: 2017-01-25
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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  • TV (total variation) image noise removal method based on noise priori constraint
  • TV (total variation) image noise removal method based on noise priori constraint
  • TV (total variation) image noise removal method based on noise priori constraint

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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 invention belongs to the technical field of digital image processing, provides a TV (total variation) image noise removal method based on noise priori constraint and can improve the noise detection accuracy and well protect image structural information. The technical scheme is that the TV image noise removal method based on the noise priori constraint comprises the following steps: step 1) inputting a noise-containing image I; step 2) enabling f to be an original sharp image; step 3) performing impulse noise influence on an image u in transmission and storage processes, and representing an image polluted by mixed noise with g; step 4) estimating noise positions with an ROAD (rank-ordered absolute difference) statistical method; step 5) constructing a TV-ROAD iteration noise removal model; step 6) solving an equation shown in the specification according to a noise removed image f obtained in the previous step to obtain a two-value matrix vector b. The method is mainly applied to 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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IPC IPC(8): G06T5/00
CPCG06T5/70
Inventor 冀中赵硕刘立
Owner TIANJIN UNIV
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