Data compression algorithms reduce file sizes by eliminating redundancy through three main approaches: Run-Length Encoding (RLE) converts consecutive identical data into counts and values (e.g., AAA BBB becomes 3A3B), Huffman Coding assigns shorter bit sequences to frequently occurring characters and longer sequences to rare ones, and LZW builds a dictionary of repeating patterns to replace them with shorter codes, enabling efficient compression for files like GIFs and ZIPs.
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#ALGO 0129 - The Magic of Compression? A Deep Dive into Huffman, LZW, RLE Algorithms!追加:
The secret to sending hundreds of MB files in seconds.
It's compression algorithms.
Compression is a technology that reduces size by finding data redundancy.
Shall we explore the three core algorithms?
First, run-length encoding.
It converts consecutive data into counts and values.
A A A B B B becomes 5A3B.
It's effective for images with many consecutive pixels.
Second, Huffman coding.
It varies the code length based on character frequency.
Frequently used characters are converted to short bits, while rare ones to long bits, reducing overall size.
Third, the LZW algorithm.
It finds repeating patterns and creates a dictionary for compression.
New patterns are registered in the dictionary and replaced by short numbers upon reappearance.
It's key for GIFs and ZIPs.
Thanks to these technologies, we can save storage space and enable fast transfers.
Compression algorithms that lighten data.
Discover more IT knowledge by subscribing.
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