Data Compression
DATA COMPRESSION
The word data is in general used to mean the information in digital form on which computer programs operate, and compression means a process of removing redundancy in the data. By 'compressing data', we actually mean deriving techniques or, more specifically, designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms, including both compression and decompression.
Data Compression means encoding the information in a file in such a way that it takes less space.
Compression is used just about everywhere. All the images you get on the web are compressed, typically in the JPEG or GIF formats, most modems use compression, HDTV will be compressed using MPEG-2, and several file systems automatically compress files when stored, and the rest of us do it by hand. The task of compression consists of two components, an encoding algorithm that takes a message and generates a “compressed” representation (hopefully with fewer bits), and a decoding algorithm that reconstructs the original message or some approximation of it from the compressed representation.
Compression denotes compact representation of data.
Examples for the kind of data we typically want to compress are e.g. * text * source-code * arbitrary files * images * video * audio data * speech
Why do we need compression ?
Compression Technology is employed to efficiently use storage space, to save on transmission capacity and transmission time, respectively. Basically, its all about saving resources and money. Despite of the overwhelming advances in the areas of storage media and transmission networks it is actually quite a surprise that still compression technology is required. One important reason is that also the resolution and amount of digital data has increased (e.g. HD-TV resolution, ever-increasing sensor sizes in consumer cameras), and that there are still
The word data is in general used to mean the information in digital form on which computer programs operate, and compression means a process of removing redundancy in the data. By 'compressing data', we actually mean deriving techniques or, more specifically, designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms, including both compression and decompression.
Data Compression means encoding the information in a file in such a way that it takes less space.
Compression is used just about everywhere. All the images you get on the web are compressed, typically in the JPEG or GIF formats, most modems use compression, HDTV will be compressed using MPEG-2, and several file systems automatically compress files when stored, and the rest of us do it by hand. The task of compression consists of two components, an encoding algorithm that takes a message and generates a “compressed” representation (hopefully with fewer bits), and a decoding algorithm that reconstructs the original message or some approximation of it from the compressed representation.
Compression denotes compact representation of data.
Examples for the kind of data we typically want to compress are e.g. * text * source-code * arbitrary files * images * video * audio data * speech
Why do we need compression ?
Compression Technology is employed to efficiently use storage space, to save on transmission capacity and transmission time, respectively. Basically, its all about saving resources and money. Despite of the overwhelming advances in the areas of storage media and transmission networks it is actually quite a surprise that still compression technology is required. One important reason is that also the resolution and amount of digital data has increased (e.g. HD-TV resolution, ever-increasing sensor sizes in consumer cameras), and that there are still