Which leads me into my next topic. Images were first coded in a very simple format, you simply read off the index values for each pixel and wrote them into a file, with some way to tell how wide and tall the image was, and how to figure out which index value belonged to which pixel. These files were very easy to encode and decode, and they had another feature, they were fast because the algorithms for reading and writing them were very simple. But as images gained more and more color depth and as resolutions increased, file sizes also increased geometrically, everyone was tired of getting messages that an image would take hours to transfer or that their diskette drives were too small to hold a given image. You've just compressed the information needed to tell someone else how to get to your house by using the fact that once they get on Rte 111 they don't have to do anything else until they get to Rte 61.
Compression is the removal of redundant information.
That's it, and unless your're begging for a headache, that's all you need to know. Ah, so you've heard of these. In other words, I don't lose information using this compression method. Our minds are so good at recognizing patterns from incomplete data that even when we looked at the black and white image of the rose, our mind still identified it as a rose, regardless of the fact that there was no color and much of the information was missing. The downside to lossy compression is that if you keep storing and retrieving an image using lossy compression, it gradually loses it's crispness and clarity.