The impact of bandwidth depends upon channel capacity. Two popular channels are ordinary telephone lines and cellular phones. Efficient use of bandwidth can be accomplished in many ways, but source encoding, of which lossy compression is a subset, is a critical method for meeting bandwidth constraints. Source coding is a way to define a good ordering of data so that the pieces of lowest contribution to quality are discarded first. Speed is determined by how fast the source coding algorithm runs and how quickly the information can be transmitted within the available bandwidth.
Good compression involves intensive computations.
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.