A fast algorithm for high-resolution acoustic image measurement using polar coordinate deconvolution

For the huge computational complexity caused by the two-dimensional shift-variant specialty of point spread function (PSF) in two-dimensional deconvoluted acoustic image measurement, this paper proposes a fast algorithm of acoustic image measurement using polar coordinate deconvolution that separates azimuth and distance domain to make a dimension-reduced processing. The proposed method converts the two-dimensional shift-variant deconvolution into two one-dimensional deconvolutions, and utilizes the approximate spatial shift-invariant characteristic of the one-dimensional deconvolution in the azimuth domain at the same time. By selecting the shift-invariant model to realize the deconvolution here, only the shift-variant deconvolution is conducted in the distance domain, thereby reducing the PSF storage space and computational complexity. The results of simulation and experimental data processing show that the proposed method significantly reduces the computational complexity with the similar performance compared to the original two-dimensional shift-variant deconvolution algorithm.