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An Image Denoising Method Based on Improved Orthogonal Matching Pursuit

An orthogonal matching tracking and image technology, applied in the field of image processing, can solve problems such as excessive phenomenon, matching tracking process judgment, unclear image edges, etc., to achieve the effect of improving accuracy and increasing the support set

Active Publication Date: 2021-05-07
NANJING UNIV OF SCI & TECH
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Problems solved by technology

They all implement the orthogonal matching pursuit algorithm, but they do not strictly judge the matching pursuit process, and the residual r will produce excessive phenomena during the iterative update process, resulting in unclear edges in the image

Method used

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  • An Image Denoising Method Based on Improved Orthogonal Matching Pursuit
  • An Image Denoising Method Based on Improved Orthogonal Matching Pursuit
  • An Image Denoising Method Based on Improved Orthogonal Matching Pursuit

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Embodiment 1

[0066] Firstly, the infrared and visible light images are collected by using the infrared focal plane and its control module or the visible light CCD, and the images are input into the computer to obtain the infrared and visible light images; in order to evaluate the effectiveness of the improved orthogonal matching pursuit algorithm, a simulation experiment is carried out. The experiment is based on MATLAB R2014b software, and the PC is configured with CPU 2.4GHz and memory 4G.

[0067] In order to denoise the infrared images and visible light images, two sets of experiments were carried out. The original image is figure 2 (a) to (d), the pixel size is 320*240.

[0068] image 3 (a)~(d) are the infrared image 1 that contains noise variance and is 30, the denoising effect comparison chart of traditional mean filter, orthogonal matching algorithm, algorithm of the present invention; Figure 4 (a)~(d) are the infrared image 1 that contains noise variance and is 45, the denoi...

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Abstract

The invention discloses an image denoising method based on improved orthogonal matching pursuit. The steps of the method are as follows: first, the image is digitized, and each pixel in the image is regarded as an atom; then the correlation coefficient is calculated by the absolute value of the inner product between the residual r and each atom in the measurement matrix Φ, and This selects L values ​​and stores the index values ​​of these L values ​​into the index matrix A m In , the measurement matrix Φ is updated until the residual is small enough to satisfy the condition, and the final residual is smaller than the previous residual, and the image is reconstructed according to the obtained residual to achieve denoising. The present invention performs sparse coding of the signal while sampling the signal, utilizes the sparsity of the signal itself to realize the sparse decomposition and reconstruction of the signal, retains the detailed features of the image, and improves the denoising precision.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image denoising method based on improved orthogonal matching pursuit. Background technique [0002] Image noise is useless information in the image, which will reduce the image quality. In the process of image acquisition and transmission, noise often becomes the main obstacle, destroying the integrity of the image, and has a great impact on the use value of the image. . Therefore, it is an indispensable and important link to extract useful signals to suppress noise, improve image quality, and prepare for subsequent higher-level processing. Image denoising is to preserve the useful information in the image, eliminate or reduce the interference and noise in the image. [0003] At present, the more mature image denoising methods can be divided into the following categories: [0004] (1) Spatial domain and transform domain processing methods [0005] Spatial domain p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 刘磊张壮李业飞宋佳晓陈旭
Owner NANJING UNIV OF SCI & TECH
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