While other techniques are known to give improvements over JPEG, these techniques are typically far too complex to implement in the low-cost hardware that dominates the multimedia compression market, and also fall short of the performance offered by the UCLA algorithm. By contrast, stack-run coding can be simply implemented in software or hardware. The UCLA team also is exploring the application of stack-run coding to other forms of electronic data compression. Image compression techniques can be either lossy or lossless. Lossy compression results in a reconstructed image that is close, but not identical, to the original image.
Lossless compression produces a reconstructed image that is an exact copy of the original.
Because lossy compression allows a much greater reduction in the size of the data, it is used for applications such as direct broadcast satellite where some subtle differences between the original and reconstructed images can be tolerated. However, Villasenor noted that stack-run coding is helping lossy compression by improving the lossless step in the process. For applications where lossless compression is important, such as digital medical image archiving, stack-run also could play a role. Basically, this can compress any list of numbers very efficiently. The UCLA team has applied for a patent on stack-run coding and is currently negotiating with several companies for licensing arrangements.