Experimental study on the application of a compressed-sensing (CS)-based deblurring method in x-ray nondestructive testing and its image performance

Abstract We investigated the compressed-sensing (CS)-based deblurring framework incorporated with the total-variation (TV) regularization penalty for effective image deblurring of high accuracy in x-ray imaging. We implemented the proposed algorithm and performed a systematic experiment to demonstrate its viability for image deblurring in x-ray nondestructive testing. We obtained x-ray images of several selected electronic components at an x-ray tube condition of 80 kVp and 1.25 mAs and investigated the imaging characteristics in terms of the noise power spectrum and the modulation. We expect the proposed deblurring method to be applicable to improve the image characteristics considerably in x-ray nondestructive testing.

[1]  Long Quan,et al.  Image deblurring with blurred/noisy image pairs , 2007, SIGGRAPH 2007.

[2]  Aggelos K. Katsaggelos,et al.  Parameter Estimation in TV Image Restoration Using Variational Distribution Approximation , 2008, IEEE Transactions on Image Processing.

[3]  Robert D. Nowak,et al.  An EM algorithm for wavelet-based image restoration , 2003, IEEE Trans. Image Process..

[4]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[5]  Qiang Wu,et al.  Image deblur in gradient domain , 2010 .

[6]  Lei Zhu,et al.  Compressed sensing based cone-beam computed tomography reconstruction with a first-order methoda). , 2010, Medical physics.

[7]  Ehsan Samei,et al.  An experimental comparison of detector performance for direct and indirect digital radiography systems. , 2003, Medical physics.

[8]  Ting-Zhu Huang,et al.  The Implementation of LSMR in Image Deblurring , 2014 .

[9]  Kunio Doi,et al.  A simple method for determining the modulation transfer function in digital radiography , 1992, IEEE Trans. Medical Imaging.

[10]  John M. Boone,et al.  Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers , 2011, Medical Image Anal..

[11]  Jin Sung Kim,et al.  Fast compressed sensing-based CBCT reconstruction using Barzilai-Borwein formulation for application to on-line IGRT. , 2012, Medical physics.

[12]  Xin Li,et al.  Fine-Granularity and Spatially-Adaptive Regularization for Projection-Based Image Deblurring , 2011, IEEE Transactions on Image Processing.

[13]  Peyman Milanfar,et al.  Deblurring Using Regularized Locally Adaptive Kernel Regression , 2008, IEEE Transactions on Image Processing.