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Ultrasonic imaging of materials often requires a large amount of data collection. Therefore, it is desirable to use data compression techniques to facilitate the analysis and remote access of ultrasonic information. The correct data representation is paramount to the accurate analysis of the geometric shape, size, and orientation of the ultrasonic reflector, as well as to the determination of the properties of the propagation path. In this study, we analyze a successive parameter estimation technique (based on the continuous wavelet transform) to deal with the compression and denoising of ultrasonic signals. The algorithm is applied to both simulated and experimental ultrasonic signals for data compression and material characterization. This technique achieves data compression ratios of up to 95% and signal-to-noise ratios improvement beyond 30 dB.