However, lossless compression does provide for more efficient storage when it is imperative that all the information stored in an image should be preserved for future use. The resulting compressed file may still be large and unsuitable for network dissemination. Lossless compression techniques can reduce the size of images by up to half. An image viewed after lossless compression will appear identical to the way it was before being compressed. Redundancy reduction, used during lossless encoding, searches for patterns that can be expressed more efficiently. It relies on two main strategies: redundancy reduction and irrelevancy reduction. Compression allows a larger number of images to be stored on a given medium and increases the amount of data that can be sent over the internet. Margot Note, in Managing Image Collections, 2011 CompressionĬompression algorithms reduce the number of bytes required to represent data and the amount of memory required to store images. For example, the recording audio or video data from some real-time programs may need to be recorded directly to a limited computer storage, or transmitted to a remote destination through a narrow signal channel.ĭepending on specific problems, we sometimes consider compression and decompression as two separate synchronous or asynchronous processes. For example, movies, photos, and audio data are often compressed once by the artist and then the same version of the compressed files is decompressed many times by millions of viewers or listeners.Īlternatively, the efficiency of the compression algorithm is sometimes more important. In many practical cases, the efficiency of the decompression algorithm is of more concern than that of the compression algorithm. However, as a reader, you should always make sure that you know the decompression solutions as well as the ones for compression. In this book, we sometimes do not even discuss the decompression algorithms when the decompression process is obvious or can be easily derived from the compression process. When compression algorithms are discussed in general, the word compression alone actually implies the context of both compression and decompression. Ida Mengyi Pu, in Fundamental Data Compression, 2006 1.1.2 DecompressionĪny compression algorithm will not work unless a means of decompression is also provided due to the nature of data compression. They often use proprietary algorithms that are better than the versions offered here and make an ideal first pass for any encryption program. How to Use It Many compression programs available for all computers. Although I don't know how to figure out the mapping between the letters and the bits in the Huffman algorithm, I don't believe it would be hard to figure out. This may not be necessary because both parties could agree on such a table in advance. Most compression algorithms transmit the table or dictionary at the beginning of the file. That is, there is a more even distribution of the data. The Disguise Compression algorithms generally produce data that looks more random. The compression algorithms can also be useful when they're used to produce mimicry by running the compression functions in reverse. This can increase their entropy and make the files appear more random because all of the possible bytes become more common. Compression algorithms are normally used to reduce the size of a file without removing information.
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