Optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction

A technology for compressing and reconstructing ultrasonic signals, applied in electrical components, complex mathematical operations, code conversion, etc., to achieve accurate reconstruction and good reconstruction effects.

Pending Publication Date: 2022-04-29
ZHONGBEI UNIV
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Problems solved by technology

[0004] In order to solve the problem of how to efficiently store and transmit data in CMUT ultrasonic signal acquisition, the present invention proposes an optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction

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  • Optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction
  • Optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction
  • Optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction

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[0017] In order to make the object, technical solution and effect of the present invention clearer, the implementation manner of the present invention will be described in detail below in conjunction with the accompanying drawings and specific examples.

[0018] A method for selecting optimal wavelet sparse basis in CMUT ultrasonic signal compression reconstruction, comprising the steps of:

[0019] a) Collect the CMUT ultrasonic A-scan signal reflected by the measured object through the CMUT ultrasonic detection system for subsequent optimization analysis; specifically: the CMUT ultrasonic detection system includes: a host controller, a CMUT probe and a data acquisition system; specific operation methods It is: the CMUT linear array probe transmits the real-time CMUT ultrasonic A-scan signal reflected by the measured object to the host controller, extracts and stores the CMUT ultrasonic A-scan signal including the target position for the next step of reconstruction optimizatio...

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Abstract

The invention discloses an optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction, and belongs to the field of CMUT ultrasonic signal compression and reconstruction. The method comprises the following steps: firstly, acquiring a CMUT ultrasonic A scanning signal reflected by a detected object through a CMUT ultrasonic detection system for subsequent optimization analysis; then selecting four common wavelet sparse bases to carry out sparse transformation on the CMUT ultrasonic A scanning signals under different decomposition layer numbers; secondly, a random Gaussian matrix is selected as a sensing matrix for compression reconstruction, an orthogonal matching pursuit algorithm is adopted to reconstruct the sparse A scanning signal, and an optimal wavelet sparse base is evaluated and selected; and finally, carrying out compression reconstruction on the sparse CMUT ultrasonic A scanning signal under different compression ratios, and evaluating the reconstruction optimization effect of the signal under different compression ratios. According to the method, the signal compression rate is improved on the premise of ensuring the reconstruction precision of the ultrasonic signal, the problem of large storage data volume in the acquisition of the CMUT ultrasonic signal is solved, the signal receiving data volume can be effectively reduced, and the signal reconstruction optimization efficiency is improved.

Description

technical field [0001] The invention belongs to the field of CMUT ultrasonic signal compression and reconstruction, in particular to an optimal wavelet sparse base selection method in CMUT ultrasonic signal compression and reconstruction. Background technique [0002] Capacitive micromachined ultrasonic transducers (CMUTs) have received more and more attention and applications due to their small size, low power consumption, high integration, and wide bandwidth. With the increasingly higher requirements for image clarity in the field of ultrasonic imaging in recent years, the amount of data collected by the CMUT ultrasonic testing system has doubled, and how to efficiently store and transmit data has become an urgent problem to be solved. [0003] Compressed sensing theory was proposed by E.J.Candes, J.Romberg, T.Tao and D.L.Donoho et al. It has been effectively applied in the fields of signal processing, ultrasound imaging and image processing. Compressed sensing theory bre...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/14H03M7/30
CPCG06F17/148H03M7/3062
Inventor 邵星灵张文栋杨玉华张甜雷淼武洋
Owner ZHONGBEI UNIV
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