For real-time systems, algorithm speed plays a significant role in determining the best compression method. The faster data must be compressed, the harder it is to find effective methods for transforming the image into an ordering that results in high compression. Sometimes, the best algorithms require a processing time many orders of magnitude greater than the actual number of pieces of information thus becoming prohibitive even for offline use. The solution is to find fast approximations to the best methods. Efficient approximation techniques are the key to both speed and quality in compression performance.
Channel reliability is how often a piece of information arrives without error.
Channel reliability restricts available bandwidth. Compression multiplies the impact of an error, and is a limiting factor to the susceptibility of the compressed data stream to errors and the ability to get the data through the channel fast. With appropriate prioritizing and formatting of the compressed data, remaining or added features of the data can be used efficiently to improve the robustness of the data, and, hence, improve the usable bandwidth or compression ratio.