Data compression is key to reducing file sizes for efficient storage and transmission, without sacrificing content. It involves techniques like Huffman Coding and the Burrows-Wheeler Transform to eliminate redundancy and irrelevancy. The choice between lossless and lossy compression depends on the need for data integrity versus efficiency, impacting multimedia, internet use, and system performance.
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Data compression is a crucial concept in computer science that involves reducing data file size without compromising its original content
Reducing redundancy
Data compression techniques work by identifying and eliminating redundancy, replacing repeated data elements with shorter references
Removing irrelevancy
Data compression also involves removing data that is not essential for the intended use, known as irrelevancy
There are two primary types of data compression: lossless and lossy, each with its own advantages and applications
Huffman Coding is a widely used technique that assigns shorter codes to more frequent characters
The Deflate algorithm combines LZ77 and Huffman coding for efficient compression
RLE is a simple algorithm that replaces sequences of the same data values with a count and a single value
BWT is a more complex algorithm that reorganizes data for better compression
The choice of algorithm depends on the type of data and the requirements for compression efficiency and data integrity
Data compression is commonly used in audio and video files to save storage space and facilitate faster transmission
GZIP compression
GZIP is a popular protocol for compressing web data and reducing page load times
MIME encoding
MIME encoding is used for email to reduce bandwidth usage
The choice between lossless and lossy compression depends on the trade-off between data size and quality
Data compression can improve system performance by reducing the amount of data to be processed and stored, but it must be balanced with the computational cost
The challenge lies in finding the right balance between reducing data size and maintaining acceptable quality for the intended audience and purpose
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Compression methods save space and aid in data transfer by removing ______ and ______ from files.
redundancy
irrelevancy
01
Lossless compression applications
Used for text, executables, scientific/medical data where integrity is critical.
02
Lossy compression trade-off
Accepts information loss for greater size reduction, suitable for multimedia.
