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Split Spectrum Processing (SSP) improves the detection of ultrasonic echoes. Generally, this method uses an algorithm named minimization. One limitation of this processing is the fact that the spectrum of echoes must be known and invariant. That restricts the field of SSP when ultrasound waves are attenuated. In this work, we propose a new scheme for the minimization process, allowing the ultrasonic investigation in absorbing material. We give an example of this method applied to a thermal spray polymer.

International audience; In this paper a fusion algorithm for the detection of specular echoes blurred by coloured Gaussian noise is proposed. The phase and energy criteria, characteristic of these echoes, are handled separately. First, the detection capabilities of split spectrum (phase) and short time Fourier transform spectrogram (energy) are compared theoretically and experimentally. Second, the new algorithm based on mathematical morphology operators using both time-frequency representations is proposed. In the last part our method is shown to be more robust than absolute minimisation split spectrum processing.

International audience; A split spectrum processing technique using a novel moving bandwidth minimization (MBM) method was developed to detect multiple specular targets having different spectral characteristics. Mathematical morphology (MM) algorithms were also implemented in order to compare the results. An experimental approach to optimal parameter determination is described. These non-linear filtering methods are applied to medical in vivo imaging to illustrate specular detection and signal to noise ratio (SNR) enhancement.