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Seismic signal random noise attenuation method, terminal equipment and storage medium
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A seismic signal, random noise technology, applied in the field of image processing, to achieve good denoising performance, improve robustness, and improve the effect of difference
Inactive Publication Date: 2021-04-16
MINNAN NORMAL UNIV
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[0004] The present invention aims to provide a seismic signal random noise attenuation method based on overlapping group sparse generalized total variation to solve the problems existing in the above-mentioned existing seismic signal denoising methods
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[0028] To further illustrate the various embodiments, the present invention is provided with accompanying drawings. These drawings are a part of the disclosure of the present invention, which are mainly used to illustrate the embodiments, and can be combined with related descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those skilled in the art should understand other possible implementations and advantages of the present invention.
[0029] 1. Preliminary knowledge:
[0030] 1.1 Second-order TGV model
[0031] The standard second-order TGV model is defined as formula (1). For the convenience of discussion, it is assumed here that the processed image is a square matrix.
[0032]
[0033] in Indicates the desired denoised image, is the observed seismic signal image, It is the intermediate variable of the TGV regular term. is the gradient operator, Represents the transverse gradient operator,...
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Abstract
The present invention relates to a seismic signal random noise attenuation method based on overlapping group sparse generalized total variation. The method comprises the following steps: S1, inputting a seismic signal graph G to be denoised; S2, initializing the parameters in the solution output image model ; S3, calculated to get F (k) , F (k) is the seismic signal map obtained by k iterations, and judges whether ||F (k+1) -F (k) || 2 / ||F (k) || 2 >tol, if satisfied, go to step S11, otherwise go to step S4; update F, V x , V y ; S5, judging whether it is satisfied, if it is satisfied, go to step S6, otherwise go to step S8; S6, use the formula to update S7, n=n+1, return to step S5; S8, calculate S9, use the formula to update S10, k= k+1, return to step S3; S11, output the denoised seismic signal map F. The method of the present invention makes full use of the neighborhood similarity of the first-order and second-order gradients of the image, improves the difference between the smooth area and the boundary area, thereby improving the robustness of the denoising algorithm, and obtaining better denoising than the classic TGV performance.
Description
technical field [0001] The invention relates to the field of image processing, in particular to a random noise attenuation method of seismic signals based on overlapping group sparse generalized total variation, terminal equipment and storage media. Background technique [0002] There are a lot of random noise in the actual seismic signal, such as Gaussian noise, gamma noise and so on. Total variation regularization (Total variation, TV) has been proved to be a kind of regularization that effectively removes random noise. Since it was proposed by Rudin et al., it has attracted extensive attention of scholars. The full variational regularization term fully exploits the horizontal and vertical gradient information of the two-dimensional image, and fits the prior knowledge of natural images such as local smoothness and gradient sparseness. It is widely used in seismic image denoising, seismic wave impedance inversion, weak and small Target detection, super-resolution analysis ...
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