One widely us data compression algorithm is the Deflate algorithm, which combines both LZ77 (Lempel-Ziv 77) and Huffman coding. Here’s an overview of how it works:
Deflate Compression Algorithm
- LZ77 Compression:
- In the first step, the Deflate algorithm applies LZ77 compression, which is a dictionary-bas compression method. It scans through the input data and identifies repeat sequences of characters.
- For each sequence encountere LZ77 encodes it as a pair of values: the distance to the start of the sequence in the already processedata (backward distance) and the length of the sequence.
- These pairs are then stor as a series of literals and length-distance pairs.
- Huffman Coding:
- In the second step, Deflate applies Huffman coding, a variable-length prefix coding technique that assigns shorter codes to more frequent symbols in the input data.
- Huffman coding operates on the output of the LZ77 compression step, which consists of literals (individual characters) and length-distance pairs.
- First, Deflate builds a frequency table of literals and length-distance pairs.
- Next, it constructs a Huffman tree bas on the frequency table, where more frequent symbols have shorter codewords and less frequent symbols have longer codewords.
- Finally, it encodes the symbols using the Huffman codes and outputs the compress data stream.
Compression Process:
- Input Data: The input data is divid into blocks or streams of bytes.
- LZ77 Compression: The Deflate algorithm searches for repeat sequences of characters within the input data and replaces them with shorter references to previous occurrences.
- Huffman Coding: The compressed output from the LZ77 step is then further compressed using Huffman coding. This step assigns variable-length codes to the symbols (literals and length-distance pairs) based on their frequency of occurrence.
- Output: The compressed output consists of a New Zealand Telemarketing Data sequence of bits, representing the compressed version of the input data.
Decompression:
- Huffman Decoding: The compress data stream Phone Number SG is decod using the Huffman tree constructed during compression. This step converts the variable-length Huffman codes back into the original symbols.
- LZ77 Decompression: The output of the Huffman decoding step is process to reconstruct the original data. Length-distance pairs are used to locate and copy repeat sequences from previously decoded data.
- Output: The final output is the decompress version of the original input data.
Applications:
- File Compression: Deflate is widely us in file compression formats such as ZIP, gzip, and zlib.
- HTTP Compression: Deflate compression is us in HTTP compression to reduce the size of web content transferr between servers and clients, improving website performance and rucing bandwidth usage.
- Data Transmission: Deflate compression can be us to compress data before transmission over networks, rucing data transfer times and bandwidth usage.
Conclusion:
The Deflate compression algorithm, with its combination of LZ77 and Huffman coding, provides efficient compression of data with a good balance of compression ratio and spe. It is widely adopt in various applications for file compression, data transmission, and web optimization, making it an essential component of modern computing systems.
