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Wavelet-based multi-scale decomposition method

A multi-scale decomposition and scaling function technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as splicing errors and failures, and achieve the effect of reducing data volume and reducing differences

Pending Publication Date: 2021-06-11
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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AI Technical Summary

Problems solved by technology

Different from the 3D data registration stitching at a single scale, the difference in information content, resolution, and richness of details in the corresponding overlapping parts of cross-scale data often leads to stitching errors or even failures

Method used

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  • Wavelet-based multi-scale decomposition method
  • Wavelet-based multi-scale decomposition method
  • Wavelet-based multi-scale decomposition method

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Embodiment Construction

[0022] Such as figure 1 As shown, a wavelet-based multi-scale decomposition method includes the following steps:

[0023] (1) Store the point cloud data as 2.5D, that is, store the Z coordinates of the point cloud data in the form of pixel values, and process the point cloud data by processing two-dimensional images;

[0024] (2) Filter by wavelet to separate high frequency from low frequency;

[0025] (3) Project the 2.5D image onto the scale function and wavelet function;

[0026] (4) carry out low-pass filtering, represent the frequency image with wavelet by step (3), take out the projection that both parts are all on the scaling function, i.e. the low-frequency data of the image;

[0027] (5) After filtering in step (4), the low frequency is reserved, and the low frequency signal is projected onto the inverse transformation kernel by the retained low frequency signal to perform image reconstruction;

[0028] (6) Reduce the difference by downsampling and upsampling throu...

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Abstract

The invention discloses a wavelet-based multi-scale decomposition method. The method comprises the following steps: (1) storing point cloud data as 2.5 D; (2) filtering is carried out in a wavelet mode, and high frequency and low frequency are separated; (3) projecting the 2.5 D image to a scale function and a wavelet function; (4) carrying out low-pass filtering, representing the frequency image by using the wavelet in the step (3), and taking out the projections of the two parts on a scale function, namely low-frequency data of the image; (5) through filtering in the step (4), reserving low frequency, performing projection on the inverse transformation kernel through reserved low-frequency signals, and performing image reconstruction; (6) reducing the difference in a down-sampling and up-sampling mode through a pyramid method; and (7) repeating the steps (3)-(6) until the resolution of the microscopic measurement data is reduced to the specified requirement. According to the invention, the difference between the microscopic measurement data volume and the structured light measurement data volume can be reduced.

Description

technical field [0001] The invention relates to the technical field of structured light measurement and microscopic measurement, in particular to a wavelet-based multi-scale decomposition method. Background technique [0002] Cross-scale measurement has broad application requirements in the fields of machinery manufacturing, aerospace, tool preparation, and geoscience surveying. With the continuous advancement of modern precision manufacturing technology, the manufactured products often have cross-scale morphology characteristics. Therefore, there are also requirements for measurement technology: while ensuring the accuracy of large-scale overall contour measurement, it is necessary to ensure that small-scale local regions of interest have higher accuracy and richer details. However, due to the limitation of a single measurement method, the requirements of both aspects cannot be taken into account. The data measured by the large field of view method often have low resoluti...

Claims

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Application Information

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IPC IPC(8): G06T7/50
CPCG06T7/50G06T2207/10028G06T2207/20016G06T2207/20064G06T2207/20024
Inventor 崔海华田威汪千金王宝俊张益华
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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