Use Sampled Data Compression In Your ISM Applications

ISM applications have distinctive channel counts, sample rates, dynamic range, compression mode, and platform requirements that differ substantially from speech, audio, and video applications. CT scanner channel counts are among the highest in manmade systems. For instance, the Toshiba Aquilion ONE CT scanner contains more than 300,000 analog-to-digital converter (ADC) channels.

The per-channel CT sample rates are relatively low at 3 to 10 ksamples/s, but the dynamic range for CT is 20 bits or more. 4D ultrasound will use nearly 2000 transducers, each sampled at 50 Msamples/s and 12 bits per sample. So a compression algorithm for ISM applications has to compress between 10 Msamples/s (lowspeed ultrasound applications) and 60 Gsamples/s (high-end oscilloscopes) per analog-to-digital channel.

Because of the large variation in channel counts, an ISM compression algorithm should be scalable in both directions. The algorithm should scale down so, for example, a single FPGA or ASIC compression instantiation operating at 250 Msamples/s could be configured to compress 10 channels at 25 Msamples/s or 25 channels at 10 Msamples/s. The algorithm should also scale up so, for instance, a 2-Gsample/s sample stream could be compressed in an ASIC or FPGA using eight instantiations of the same 250-Msample/s compression core.

ISM users will benefit from selecting lossless or lossy compression modes, unlike today’s speech, audio, and video compression algorithms that only offer lossy compression. ISM engineers want to begin using compression with the guaranteed signal quality that lossless compression offers. Once they and their customers realize their sampled data signals contain imperfections and that their own DSP processing can tolerate small errors, ISM users can experiment with lossy modes because the compression ratios are higher.