A Sparse Reconstruction Algorithm for Ultrasonic Images in Nondestructive Testing

Sensors

Giovanni Alfredo Guarneri¹  Daniel Rodrigues Pipa²  Flávio Neves Junior²  Lྫྷia Valéria Ramos de Arruda²  Marcelo Victor Wüst Zibetti² 

[1] Graduate School on Electrical Engineering and Applied Computer Science, Federal University of Technology—Paraná (UTFPR), Curitiba-PR 80230-901, Brazil;

关键词: ultrasonic imaging;    image reconstruction;    sparse reconstruction;    nonquadratic regularization;    nondestructive testing;   

DOI  :  10.3390/s150409324

来源: mdpi

【 摘 要 】

Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l₁ regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan—about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR).

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.