Compression techniques for IoT enabled handheld ultrasound imaging system

Received echo signals of transducer in ultrasound imaging have a high dynamic range of 12 bits and hence cannot be displayed on Cathode Ray Tube (CRT), Liquid Crystal Display (LCD) monitors of ultrasound machine. Log compression is being used to compress the data to 8 bits. Since log compression is a non linear compression it is very difficult to trace the original characteristics of the signal. In this paper various global and local compression techniques were studied as a replacement for log compression so that the dynamic range of image can be retrieved if the physician has a better monitor for display, and also ensure minimum error in the retrieved signal leading to minimum error in retrieved image. From the results it is observed that Structural SIMilarity (SSIM) of wavelet compressed image is 1.02 times more and that of gamma compressed image is 2.24 times more than log compressed image. Gamma based compression can be preferred to log and wavelet based compression, as it gives good quality image when compared with other compression techniques, but cannot be used to retrieve the statistical properties when expanded, since these statistical properties are helpful for doctors for better analysis. Wavelet based compression serves this purpose and hence is best suited for Internet of Things (IoT) enabled ultrasound system for remote diagnosis in the cloud.