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An image denoising method based on level set curvature and wavelet transform

A technology of level set curvature and wavelet transform, applied in the field of image processing, it can solve the problems of easy loss of image edges and textures, step effect in smooth areas, etc., and achieve the effect of enhancing sharp edges of images and removing noise.

Inactive Publication Date: 2019-01-18
SOUTH CHINA UNIV OF TECH
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  • Claims
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Problems solved by technology

[0003] At present, the use of partial differential equations to denoise has stronger local adaptive ability and higher flexibility than traditional methods, but it will produce a staircase effect in the smooth area
Wavelet denoising is to process the wavelet coefficients of signal and noise, the essence of which is to reduce the coefficients generated by noise, which will lead to easy loss of image details such as edges and textures

Method used

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  • An image denoising method based on level set curvature and wavelet transform
  • An image denoising method based on level set curvature and wavelet transform
  • An image denoising method based on level set curvature and wavelet transform

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Embodiment

[0043] Such as Figure 10 As shown, an image denoising method based on level set curvature and wavelet transform includes the following:

[0044] In the first step, image the high-density flexible substrate as figure 1 As shown, Gaussian noise with a mean value of 0 and a variance of 0.1 is added to obtain a noise image, and then wavelet transform is used for layering. In the present invention, the noise image is divided into two layers, and the wavelet base is selected as "coif3", specifically:

[0045] Such as figure 2 As shown, first low-pass filtering and high-pass filtering are performed on the noise-containing high-density flexible substrate image, and then down-sampling is performed to extract one out of two rows. In the wavelet transform of the first layer, four sub-bands are obtained: 1 low-frequency sub-band with LL 1 and 3 high frequency subbands HL 1 , LH 1 、HH 1 . Low frequency sub-band LL 1 It is obtained by performing horizontal and vertical low-pass fi...

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Abstract

The invention discloses an image denoising method based on level set curvature and wavelet transform, includes: performing wavelet transform stratification processing for high-density flexible substrate image containing noise, S2 extracting high-frequency component images and low-frequency component images respectively from the sliced images, S3 establishing an image level set curvature variational smoothing model for image smoothing, S4 fusing the high-frequency image after smoothing with the low-frequency image after slicing, and reconstructing to obtain the denoised image. Compared with other denoising models, the novel method of the invention has higher peak signal-to-noise ratio and higher structural similarity.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image denoising method based on level set curvature and wavelet transform. Background technique [0002] High-density flexible printed circuit boards (FICS) have the advantages of good flexibility, thin thickness, light weight, and small size, and are widely used in electronics, military and other industries. In the process of actually collecting pictures, the generation and transmission of images will be disturbed by random pulses and other noises, and when the high-density flexible printed substrate (FICS) is slightly oxidized by air but does not affect the quality of the substrate, the oxidized area can also be As a kind of noise, these noises have a serious impact on image quality detection. Image denoising is the technique of reducing any possible degradation to enhance the image, so high-density flexible printed substrate (FICS) image denoising is very important. [000...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/20064G06T5/70
Inventor 胡跃明黄丹
Owner SOUTH CHINA UNIV OF TECH
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