This
paper presents an accelerated iterative Landweber method for nonlinear
ultrasonic tomographic imaging in a multiple input multiple output (MIMO)
configuration under a sparsity constraint on the image. The proposed method introduces
the emerging MIMO signal processing techniques and target sparseness
constraints in the traditional computational imaging field, thus significantly
improves the speed of image reconstruction compared with the conventional
imaging method while producing high quality images. Using numerical examples, we
demonstrate that incorporating prior knowledge about the imaging field such as
target sparseness accelerates significantly the convergence of the iterative
imaging method, which provides considerable benefits to real-time tomographic
imaging applications.
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