4 data compression
- 1. Data Compression Methods Run-length method Huffman method Rejin Thomas B3GMCA2124 November 13, 2015 1B3GMCA2124
- 2. What is Data Compression? Data compression is the process of reducing the size of data. Benefits ◦ Reduce storage needed ◦ Reduce transmission cost / bandwidth November 13, 2015 2B3GMCA2124
- 3. Data Compression Methods Data compression is about storing and sending a smaller number of bits. There’re two major categories for methods to compress data: lossless and lossy methods November 13, 2015 3B3GMCA2124
- 4. Lossless Compression Methods . In lossless methods, original data and the data after compression and decompression are exactly the same. Redundant data is removed in compression and added during decompression. Lossless methods are used when we can’t afford to lose any data: legal and medical documents, computer programs November 13, 2015 4B3GMCA2124
- 5. The Huffman Coding developed by David Huffman. In Huffman coding, you assign shorter codes to symbols that occur more frequently and longer codes to those that occur less frequently. November 13, 2015 B3GMCA2124 5 Run-length encoding Replace consecutive repeating occurrences of a symbol by 1 occurrence of the symbol itself, then followed by the number of occurrences.
- 6. Lempel Ziv Encoding It is dictionary-based encoding Basic idea: Create a dictionary(a table) of strings used during communication. If both sender and receiver have a copy of the dictionary, then previously-encountered strings can be substituted by their index in the dictionary. November 13, 2015 6B3GMCA2124
- 7. Lempel Ziv Compression Have 2 phases: Building an indexed dictionary Compressing a string of symbols • Algorithm: Extract the smallest substring that cannot be found in the remaining uncompressed string. Store that substring in the dictionary as a new entry and assign it an index value Substring is replaced with the index found in the dictionary Insert the index and the last character of the substring into the compressed string November 13, 2015 7B3GMCA2124
- 8. Lossy Compression Methods Used for compressing images and video files (our eyes cannot distinguish subtle changes, so lossy data is acceptable). These methods are cheaper, less time and space. Several methods: JPEG: compress pictures and graphics MPEG: compress video MP3: compress audio November 13, 2015 8B3GMCA2124
- 9. Run-length encoding Simplest method of compression. How: replace consecutive repeating occurrences of a symbol by 1 occurrence of the symbol itself, then followed by the number of occurrences. The method can be more efficient if the data uses only 2 symbols (0s and 1s) in bit patterns and 1 symbol is more frequent than another. November 13, 2015 9B3GMCA2124
- 10. Huffman Coding Assign fewer bits to symbols that occur more frequently and more bits to symbols appear less often. Algorithm: ① Make a leaf node for each code symbol Add the generation probability of each symbol to the leaf node ② Take the two leaf nodes with the smallest probability and connect them into a new node Add 1 or 0 to each of the two branches The probability of the new node is the sum of the probabilities of the two connecting nodes ③ If there is only one node left, the code construction is completed. If not, go back to (2) November 13, 2015 10B3GMCA2124
- 11. Huffman Coding Example November 13, 2015 11B3GMCA2124
- 12. Huffman Coding Encoding Decoding November 13, 2015 12B3GMCA2124
- 13. References http://www.csie.kuas.edu.tw/course/cs/engli sh/ch-15.ppt CS157B-Lecture 19 by Professor Lee http://cs.sjsu.edu/~lee/cs157b/cs157b.html “The essentials of computer organization and architecture” by Linda Null and Julia Nobur. November 13, 2015 13B3GMCA2124
- 14. Data Compression QUESTION? November 13, 2015 14B3GMCA2124