Lossless compression of audio data

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Data compression is the process of representing data using less space than that required by the data's normalrepresentation. Data compression can either be "lossless", in which case the original data can be recovered exactly, or "lossy", whereby only an approximation of the original data can be recovered. Lossless data compression is appropriate for textual or other kinds of data where any modifications would have significantdetrimental effects. Lossy data compression is frequently used for image or audio data, where the degree of degradation is adjusted according to some notion of "acceptability". Lossy compression of music is currently in the public eye because of intellectual property issues surrounding the sharing of MP3 files.While lossy compression is suitable for applications such as the casual enjoyment of music, in other situations it is not appropriate.  For example, audio data such as that obtained from passive sonar systems typically has a very low signal to noise ratio (SNR); that is, the desired sound is embedded in a relatively loud environmental noise field. Further degradation of the SNR by using a lossy compression scheme may be unacceptable. Also, lossy compression techniques are often based on psycho-acoustic principles which dictate that humans will not hear certain sounds (such as, loosely speaking, a quiet sound occurring shortly before or after a louder sound); these principles are inappropriate if the audio data is to be processed by computer software.This research program will study the lossless compression of audio data, with particular attention to the following topics: (1) defining new audio data models to optimize compressability; (2) differentiating thesemodels, if beneficial, towards sonar data, music and speech; and (3) examining the tradeoffs involved with compression effort vs. decompression effort for particular compression schemes.