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Performance evaluation of DWT, DCT, and WHT for compression of ultrasonic signals

Ultrasonic imaging for industrial and medical applications requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data while maintaining the signal integrity, and to facilitate the analysis and remote access of ultrasonic information. Hence, the locally obtained ultrasonic signals can be transferred efficiently through wireless or wired communication channels or computer networks to the remotely located experts for analysis. In this study the data compression performance of the discrete wavelet transform (DWT), the discrete cosine transform (DCT), and the Walsh-Hadamard transform (WHT) is examined using simulated and experimental ultrasonic signals. Furthermore, we present results that show the relationship between the bandwidth of the ultrasonic echoes and the data compression performance. The results reveal that the DCT is best for compressing narrowband echoes while the DWT is best for compressing broadband echoes. Moreover, high fidelity signal reconstruction can be achieved with a 90% compression ratio.