A Method for Enhancement of Seismic Section Image Texture Detail

Abstract

The invention discloses a method for enhancing texture details of seismic section images. In the method, a filter is firstly designed to perform edge-preserving and noise-reduction processing on seismic section images; then, the noise-reduced image is converted from RGB space to HSI space; The luminance component I is decomposed by single-layer wavelet to generate 1 low-frequency approximate component and 3 high-frequency detail components. Multi-scale texture detail enhancement is performed on the 3 high-frequency detail components generated by single-layer wavelet decomposition, and the low-frequency approximate component is processed in the frequency domain. Low-pass filtering; perform wavelet reconstruction on the processed 3 high-frequency detail components and 1 low-frequency approximate component to generate a new brightness component I; finally, combine the new I component with H and S components, and then extract from the HSI space Convert to RGB space to obtain the seismic section image after texture detail enhancement processing. The method of the invention enhances the texture detail information of the noisy seismic profile image, and provides a basis for the accurate analysis of the seismic profile information in the next step.

Description

technical field [0001] The invention relates to a seismic section texture detail enhancement technology, specifically, a wavelet decomposition-based multi-scale seismic section image texture detail enhancement method, which belongs to the field of information processing technology. Background technique [0002] Seismic profile images have obvious texture features, and different textures represent different geological bodies, which are of great significance for the interpretation of stratigraphic profile information such as geological faults. However, in the process of generating seismic section images, the acquired seismic data is affected by external noise, and Gaussian random noise is generated in the process of seismic data processing, which makes the texture of seismic section images blurred, and even produces texture interruptions. Image interpretation causes interference, so it is of great significance to study methods for enhancing texture details of seismic section i...

AI Technical Summary

Problems solved by technology

However, in the process of generating seismic section images, the acquired seismic data is affected by external noise, and Gaussian random noise is generated in the process of seismic data processing, which makes the texture of seismic section images blurred, and even produces texture interruptions. Image interpretation causes interference, so it is of great significance to study the method of enhancing the texture details of seismic section images

[0003] At present, the texture detail enhancement methods of seismic section images are mainly conventional image enhancement methods based on various filters; these methods filter images by designing various types of filters, and their main goals are to remove noise and enhance the continuity of reflection events. At the same time, the image contrast is effectively improved to achieve the effect of seismic section image enhancement; although these image processing methods can be used to enhance the texture details of seismic section images, due to the differences between seismic section images and conventional images, conventional image processing methods cannot be directly applied to seismic In image processing, for example, the boundaries with sinusoidal features in seismic images are not as obvious as in conventional images, and the horizontally disconnected boundary information (fault information) needs to be protected, but these information will be affected to varying degrees in the conventional image filtering process. Therefore, it is necessary to propose a new method to enhance the texture details according to the characteristics of seismic section images.

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