Seismic image completion method based on information entropy norm

A seismic image and information entropy technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as inaccurate distinction, low-rank matrix, insufficient sparse description, etc., to achieve improved restoration effect and robust performance Effect

Active Publication Date: 2020-02-25
CHENGDU UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0004] The core of the method based on matrix rank reduction is to use the L1 norm of the singular value vector of the matrix to describe the low rank of seismic data, but the L1 norm description has the problem of insufficient sparse description: for example, for a=[4,4,4 ,0,0] and b=[10,1,1,0,0] two singular value vectors,

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  • Seismic image completion method based on information entropy norm
  • Seismic image completion method based on information entropy norm
  • Seismic image completion method based on information entropy norm

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Embodiment Construction

[0059] For the convenience of those skilled in the art to understand the content of the present invention, the following technologies are now explained:

[0060] Matrix completion

[0061]In 2006, Donoho proposed the famous compressed sensing theory in "DONOHO D L. Compressed sensing [J]. Information Theory, IEEE Transactions on, 2006 52(4): 1289-1306", followed by digital cameras, medical imaging, It is widely used in fields such as multimedia hybrid coding, and it is also the source of matrix completion theory. The core idea of ​​compressive sensing theory is: using a small amount of sampled data, the high-dimensional sparse original signal can be accurately restored, that is, the perception of high-dimensional sparse signal can be realized. But in many practical problems such as: text analysis, image repair, recommendation system, etc., the data that needs to be restored is often presented in a matrix. Naturally, the research object of compressed sensing extends from the ...

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Abstract

The invention discloses a seismic image completion method based on an information entropy norm. The method is applied to the field of geophysical seismic data processing. The problem that a low-rank matrix obtained through recovery based on a matrix rank reduction method is not a real low rank due to the limitation of an existing L1 norm is solved. According to the method, the objective function based on the information entropy norm replaces a nuclear norm adopted by original SVD, then the information entropy norm is used for regularizing a rank minimization item of the objective function, andfinally an iterative ADMM estimation method is used for approximate solution to obtain a low-rank matrix, so that steady recovery of a missing image is obtained.

Description

technical field [0001] The invention belongs to the field of geophysical seismic data processing, and in particular relates to a seismic data complementing technology. Background technique [0002] In the actual geophysical seismic exploration and acquisition, there are two main reasons for the lack of seismic data: (1) The surface environment of the work area (such as rivers, ponds, lakes, etc.), surface obstacles (roads, houses, bridges, etc.) ) and other influences, the layout of the geophone is often irregular; (2) due to the poor coupling effect between the geophone and the ground surface, environmental interference or the instrument itself will produce waste tracks and waste guns. With the development of seismic exploration technology, the volume of collected data is increasing. On the one hand, we hope that densely sampled data can obtain more accurate underground structures. On the other hand, considering the cost of exploration, we need to sparsely sample in the spa...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/005
Inventor 李勇陈力鑫李雪梅郝思宇马泽川陈杰王鹏飞
Owner CHENGDU UNIVERSITY OF TECHNOLOGY
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