Ultrasonic systems are widely used in imaging applications for non-destructive evaluation, quality assurance and medical diagnosis. These applications require large volumes of data to be processed, stored and/or transmitted in real-time. Therefore it is essential to compress the acquired ultrasonic radio frequency (RF) signal without inadvertently degrading desirable signal features. In this paper, two algorithms for ultrasonic signal compression are analysed based on: sub-band elimination using discrete wavelet transform; and decimation/interpolation using time-shift property of Fourier transform. Both algorithms offer high signal reconstruction quality with a peak signal-to-noise ratio (PSNR) between 36 to 39 dB for minimum 80% compression. The computational loads and signal reconstruction quality are examined in order to determine the best compression method in terms of the choice of DWT kernel, sub-band decomposition architecture and computational efficiency. Furthermore, for compressing a large amount of volumetric information, three-dimensional (3D) compression algorithms are designed by utilising the temporal and spatial correlation properties of the ultrasonic RF signals. The performance analysis indicates that the 3D compression algorithm presented in this paper offers an overall 3D compression ratio of 95% with a minimum PSNR of 27 dB.

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Processing algorithms for three-dimensional data compression of ultrasonic radio frequency signals

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