scholarly journals Pulse Peak Delay-Total Focusing Method for Ultrasonic Tomography on Concrete Structure

2021 ◽  
Vol 11 (4) ◽  
pp. 1741
Author(s):  
Hungjoo Kwon ◽  
Changbin Joh ◽  
Won Jong Chin
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Ultrasonic Pulse ◽  
Experimental Results ◽  
Ultrasonic Tomography ◽  
Data Set ◽  
Image Reconstruction Algorithm ◽  
Long Wavelength ◽  
Ultrasonic Array ◽  
Pulse Peak

An ultrasonic array device like the A1040 MIRA is used to non-destructively visualize the inside of concrete structures. A data set acquired by the ultrasonic array device is so unfocused that an image reconstruction algorithm is required to transform the data set into an understandable image. The image reconstruction algorithm like total focusing method exploits the time-of-flight of an ultrasonic pulse when focusing the image. While a high frequency ultrasonic pulse barely affects the accuracy of results, a low frequency ultrasonic pulse with a long wavelength causes an overall sagging of the resulting image around half wavelength of the pulse, which results in a poor quality of results. In this research, a modified total focusing method called pulse peak delay-total focusing method is proposed to calibrate the sagging in the resulting images due to the long wavelength of the pulse. The simulation of an ultrasonic array signal is implemented to validate the proposed method. The experimental results are compared with the simulation results to validate the proposed method. The simulation using the proposed method shows good agreement with experimental results. Analysis of results using potential damage curve and array performance indicator shows that the proposed method allows the higher accuracy, as well as the increased resolution of resulting images.

scholarly journals PySpark-Based Optimization of Microwave Image Reconstruction Algorithm for Head Imaging Big Data on High-Performance Computing and Google Cloud Platform

2020 ◽  
Vol 10 (10) ◽  
pp. 3382
Author(s):  
Rahmat Ullah ◽  
Tughrul Arslan
Keyword(s):  
Image Reconstruction ◽  
High Performance Computing ◽  
High Performance ◽  
Reconstruction Algorithm ◽  
Apache Spark ◽  
Cloud Platform ◽  
Data Set ◽  
Image Reconstruction Algorithm ◽  
Performance Computing ◽  
Microwave Image

For processing large-scale medical imaging data, adopting high-performance computing and cloud-based resources are getting attention rapidly. Due to its low–cost and non-invasive nature, microwave technology is being investigated for breast and brain imaging. Microwave imaging via space-time algorithm and its extended versions are commonly used, as it provides high-quality images. However, due to intensive computation and sequential execution, these algorithms are not capable of producing images in an acceptable time. In this paper, a parallel microwave image reconstruction algorithm based on Apache Spark on high-performance computing and Google Cloud Platform is proposed. The input data is first converted to a resilient distributed data set and then distributed to multiple nodes on a cluster. The subset of pixel data is calculated in parallel on these nodes, and the results are retrieved to a master node for image reconstruction. Using Apache Spark, the performance of the parallel microwave image reconstruction algorithm is evaluated on high-performance computing and Google Cloud Platform, which shows an average speed increase of 28.56 times on four homogeneous computing nodes. Experimental results revealed that the proposed parallel microwave image reconstruction algorithm fully inherits the parallelism, resulting in fast reconstruction of images from radio frequency sensor’s data. This paper also illustrates that the proposed algorithm is generalized and can be deployed on any master-slave architecture.

Eminent Pixel Reconstruction Algorithm For Ultrasonic Tomography

2012 ◽  
Author(s):  
Nor Muzakkir Nor Ayob ◽  
Mohd Hafiz Fazalul Rahiman ◽  
Zulkarnay Zakaria ◽  
Ruzairi Abdul Rahim ◽  
Sazali Yaacob
Keyword(s):  
Image Reconstruction ◽  
Phase Distribution ◽  
Median Filter ◽  
Reconstruction Algorithm ◽  
Imaging Method ◽  
Ultrasonic Tomography ◽  
Two Phase ◽  
Image Reconstruction Algorithm ◽  
Component Distribution ◽  
Tomography System

Perisian rekonstruksi imej dan algoritma rekonstruksi imejnya merupakan antara kaedah penting dalam pembangunan sebuah sistem tomografi. Kerta kerja ini akan membentangkan sebuah algoritma rekonstruksi imej untuk sistem ultrasonik tomografi dua–fasa. Algoritma tersebut, dikenali sebagai algoritma Rekonstruksi Piksel Utama (RPU) dirumus berdasarkan algoritma Unjuran Balik Linear (UBL). Algoritma rekonstruksi imej yang baru ini berjaya menyerlahkan piksel berintensiti tinggi daripada piksel–piksel sekeliling di dalam imej keratan rentas yang terhasil. Algoritma RPU kemudian digabungkan pula dengan Penapis Median yang membantu menghilangkan piksel–piksel yang tidak representatif dan membantu meningkatkan mutu rekonstruksi imej. Algoritma ini adalah pilihan yang sesuai berbanding dengan algoritma UBL memandangkan seperti UBL, RPU juga merupakan teknik pengimejan yang mudah tetapi mempunyai kejayaan yang lebih tinggi dalam merekonstruksi distribusi komponen dan mampu memberikan estimasi statistik distribusi komponen dua–fasa yang lebih tepat. Kata kunci: Algoritma rekonstruksi imej; rekonstruksi piksel utama; tomografi transmisi ultrasonik, aliran dua–fasa; penapis median; distribusi komponen Image reconstruction software and its image reconstruction algorithm are an important step towards constructing a tomography system. In this paper, description on the introduction of an image reconstruction algorithm for two–phase ultrasonic tomography system is presented. The algorithm, termed as the Eminent Pixel Reconstruction (EPR) algorithm is derived based on the basic Linear Back Projection (LBP) algorithm. This new image reconstruction algorithm successfully highlights high intensity pixels from the surrounding pixels in the cross–section image. The EPR algorithm are then combined with the useful Median Filter which helps eliminate the unrepresentative pixels resulting in reduced noise on the final reconstructed image. The algorithm is also deem as a preferable choice other than the LBP algorithm since like the LBP, EPR is also a straightforward imaging method with higher success of reconstructing the component distribution and provides more accurate statistical estimation capability on the two–phase distribution. Key words: Image reconstruction algorithm; eminent pixel reconstruction; ultrasonic transmission tomography; two–phase flow; median filter; component distribution

MICROWAVE IMAGING OF EMBEDDED OBJECT USING AN ENHANCED IMAGE RECONSTRUCTION ALGORITHM

2015 ◽  
Vol 74 (20) ◽  
pp. 1793-1801
Author(s):  
Sidi Mohammed Chouiti ◽  
Lotfi Merad ◽  
Sidi Mohammed Meriah ◽  
Xavier Raimundo
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Microwave Imaging ◽  
Image Reconstruction Algorithm

scholarly journals Rotational hyperspectral scanner and related image reconstruction algorithm

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Longqiang Luo ◽  
Shuo Li ◽  
Xinli Yao ◽  
Sailing He
Keyword(s):  
Image Reconstruction ◽  
Spectral Resolution ◽  
Reconstruction Algorithm ◽  
Hyperspectral Data ◽  
Data Cube ◽  
Spatial Accuracy ◽  
Scanning Method ◽  
Image Reconstruction Algorithm

AbstractWe design and implement a compact and lightweight hyperspectral scanner. Based on this, a novel rotational hyperspectral scanner was demonstrated. Different from translational scanning, rotational scanning is a moveless and stable scanning method. We also designed a relevant image algorithm to reconstruct the image from an angular recorded hyperspectral data cube. The algorithm works well even with uncertain radial and tangential offset, which is caused by mechanical misalignment. The system shown a spectral resolution of 5 nm after calibration. Finally, spatial accuracy and spectral precision were discussed, based on some additional experiments.

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