Airborne electromagnetic data denoising method based on mathematical morphology

Abstract

The invention relates to an airborne electromagnetic data denoising method based on mathematical morphology. The airborne electromagnetic data denoising method includes: acquiring airborne electromagnetic detection data through an experiment, and combining triangular structure elements with semicircular structure elements to perform adaptive multiscale composite morphological filtering on the airborne electromagnetic date; determining a length range of the structure elements according to a minimum value and a maximum value of adjacent peak value intervals in original signals, and determining corresponding analysis scale K according to the length range; determining a height range according to a minimum value and a maximum value of signal peak values; adopting structure element sets for composite morphological operation on the original signals, and acquiring an average value as an output result. The adaptive multiscale composite morphological filtering method overcomes the defect of randomness in conventional selection of morphological filtering structure elements; by the airborne electromagnetic data denoising method, structure element type and scale can be selected adaptively according to local features and noise characteristics of signals for filtering airborne electromagnetic signals.

Description

technical field [0001] The invention relates to a data denoising method in the field of aeronautical electromagnetics, especially in the field of time domain aeronautical electromagnetics, in particular to a method for denoising data in aeronautical electromagnetics based on mathematical morphology. Background technique [0002] Airborne electromagnetic method is a kind of survey and detection method that uses aircraft as a carrier to carry out geophysical exploration. It is mainly used for rapid survey of metal ore bodies, large-scale geological mapping, hydrogeology, engineering geological exploration and environmental monitoring and other fields. [0003] Mathematical morphology is a discipline based on strict mathematical theory. It has been successfully applied in engineering practice fields such as image processing, graphic analysis, pattern recognition, computer vision, electrical energy disturbance, mechanical vibration and earthquake detection, and has attracted wide...

AI Technical Summary

Problems solved by technology

[0005] Most of the existing morphological filtering methods only use single-scale structural elements, and single-scale morphology only selects a fixed structural element for morphological analysis of the signal. Although this method is simple and easy to implement, its processing effect is extremely poor. It relies heavily on relevant prior knowledge, but accurate and effective prior knowledge is often difficult to obtain

In addition, since the signal usually contains more than one type of noise, and the noise is often not evenly distributed in the signal

[0006] None of the existing morphological filtering methods can perform complex morphological filtering on different types and intensities of noise components in structural element signals at different scales

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