File Compression Techniques
File Compression Techniques. Alex Robertson. Outline. History Lossless vs Lossy Basics Huffman Coding Getting Advanced Lossy Explained Limitations Future. History, where this all started. The Problem! 1940s Shannon- Fano coding Properties
File Compression Techniques
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File Compression Techniques Alex Robertson
Outline • History • Lossless vsLossy • Basics • Huffman Coding • Getting Advanced • Lossy Explained • Limitations • Future
History, where this all started • The Problem! • 1940s • Shannon-Fano coding • Properties • Different codes have different numbers of bits. • Codes for symbols with low probabilities have more bits, and codes for symbols with high probabilities have fewer bits. • Though the codes are of different bit lengths, they can be uniquely decoded.
Lossless vsLossy • Lossless • DEFLATE • Data, every little detail is important • Lossy • JPEG • MP3 • Data can be lost and unnoticed
Understanding the Basics • Properties • Different codes have different numbers of bits. • Codes for symbols with low probabilities have more bits, and codes for symbols with high probabilities have fewer bits. • Though the codes are of different bit lengths, they can be uniquely decoded. • Encode “SATA” S = 10 A = 0 T = 11
Prefix Rule • S = 01 A = 0 T = 00 • SATA • SAAAA • STT 01 0 00 0 No code can be the prefix of another code. If 0 is a code, 0* can’t be a code.
Make a Tree • Create a Tree A = 010 B = 11 C = 00 D = 10 R = 011
Decode • 01011011010000101001011011010 A = 010 B = 11 C = 00 D = 10 R = 011 • Violates the property: • Codes for symbols with low probabilities have more bits, and codes for symbols with high probabilities have fewer bits.
Huffman Coding • Create a Tree • Encode “ABRACADABRA” • Determine Frequencies • The two least frequent “nodes” are located. • A parent node is created from the two above nodes and it is given a weight equal to the sum of the two contain node frequencies. • One of the child nodes is given the 0 bit and the other the 1 bit • Repeat the above steps until only one node is left.
Does it work? • Re-encode • 01011011010000101001011011010 • 29 bits
It Works! 01011001110011110101100 = 23 bits ABRACADABRA = 11 character * 7 bits each = 77 bits but…
It Works… With Issues. • Header includes the probability table • Not the best in certain cases Example. ‘A’ 100 times Huffman only reduces this to 100 bits (minus the header)
Moving Forward • Arithmetic Method • Not Specific Code • Continuously changing single floating-point output number • Example
Dictionary Based • Implemented in the late 70s • Uses previously seen words as a dictionary. • the quick brown fox jumped over the lazy dog • I bought a Mississippi Banana in Mississippi.
Lossy Compression • Lossy Formula • Lossless Formula • My Sound!
Mathematical Limitations • Claude E. Shannon • http://www.data-compression.com/theory.html
Example • DEFLATE • http://en.wikipedia.org/wiki/DEFLATE
Future • Hardware is getting better • Theories are the same
Thanks You • Questions