Data Compression Essays - Archive Formats, Data Compression

Data Compression Essays - Archive Formats, Data Compression Data Compression subject = Information Theory title = Data Compression Data Compression- in beginners terms Data Compression just sounds complicated. Dont be afraid, compression is our good friend for many reasons. It saves hard drive space. It makes data files to handle. It also cuts those immense file download times from the Internet. Wouldnt it be nice if we could compress all files down to just a few bytes? There is a limit to how much you can compress a file. How random the file is, is the determining factor to how far it can be compressed. If the file is completely random and no pattern can be found, then the shortest representation of the file is the file it self. The actual proof that proves this is at the end of my paper. The key to compressing a file is to find some sort of exploitable pattern. Most of this paper will be explaining those patterns that are commonly used. Null suppression is the most primitive form of data compression that I could find. Basically, it says that if you have different fields that data is in (possibly a spread sheet), and any of them have only zeros in them, then the program just eliminates the data and goes straight from the empty data set to the next. Only one step up from null suppression is Run Length Encoding. Run length encoding simply tells you how many of what you have in a row. It would change a set of binary data like 0011100001} into what the computer reads as (2)zeros, (3)ones, (4)zeros, 1. As you can see, it works on the same basic idea of finding a series of 0s (null suppression) and 1s in this case too and abbreviating them. Once the whole idea of data compression caught on, more people started working on programs for it. From these people we got some new premises to work with. Substitutional encoding is a big one. It was invented jointly by two people: Abraham Lempel and Jakob Ziv. Most compression algorithms (big word meaning roughly program) using substitutional encoding start with LZ for Lempel-Ziv. LZ-77 is a really neat compression in which the program starts off just copying the source file over to the new target file, but when it recognizes a phrase of data that it has previously written, it replaces the second set of data in the target file with directions on how to get to the first occurrence of it and copy it in the directions place. This is more commonly called a sliding-window compression because the focus of the program is always sliding all around the file. LZ-78 is the compression that most people have in their homes. Some of the more common ones are ZIP, LHA, ARJ, ZOO, and GZIP. The main idea behind LZ-78 is a dictionary. Yet it works quite a bit like the LZ-77. For every phrase it comes across, it indexes the string by a number and writes it in a dictionary. When the program comes across the same string, it uses the associated number in the dictionary instead of the string. The dictionary is then written along side the compressed file to be used in decoding. There is a combined version of LZ-77 an LZ-78. It is called LZFG. It only writes to the dictionary when it finds the repeated phrase, not on every phrase. Then instead of LZFG replacing the second set of data with directions on how to get to the first occurrence of it, the program puts in the number reference for the dictionarys translation. Not only is it faster, but it compresses better because of the fact that it doesnt have as big of a dictionary attached. Statistical encoding is another one of the new compression concepts. It is an offshoot of the LZ family of compressors; It uses basically the same style as LZFG, but instead of assigning the numbers in order that the strings come out of the source file, statistical compressors do some research. It calculates the number of times each string is used and then ranks the string with the most number of uses at the top of the hash table. The string with the least is ranked at the bottom. (A hash table is where the rank is figured) The higher up a string is on this list, the smaller of a reference number it gets to minimize the total bit usage. This gives this compression just a slight edge on the others, but every little bit helps. (ha ha -bit- ) Beware! There are a