Title :
Sparsity aware nonlinear multichannel ultrasonic tomographic imaging
Author :
Dong, Chengdong ; Jin, Yuanwei ; Lu, Enyue
Author_Institution :
Appl. Math., Shanghai Univ. of Finance & Econ., Shanghai, China
Abstract :
This paper presents an accelerate projected steepest descent method for nonlinear ultrasonic tomographic imaging with sparsity constraints in a multiple-input multiple-output configuration. The proposed method introduces the emerging MIMO signal processing techniques and sparsity constrained image reconstruction methods to the traditional computational imaging field, thus significantly improves the speed of image formation compared with conventional imaging method while achieving high quality images. Using numerical examples, we demonstrate the success of the proposed algorithm.
Keywords :
MIMO communication; gradient methods; image reconstruction; ultrasonic imaging; MIMO signal processing techniques; computational imaging field; multiple-input multiple-output configuration; sparsity aware nonlinear multichannel ultrasonic tomographic imaging; sparsity constrained image reconstruction methods; steepest descent method; Acceleration; Acoustics; Inverse problems; MIMO; Propagation; Tomography;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th
Conference_Location :
Hoboken, NJ
Print_ISBN :
978-1-4673-1070-3
DOI :
10.1109/SAM.2012.6250473