M-Band Acoustic Data Compression
Small Business Information
One Oak Park, Cambridge, MA, 02142
Stephen P. Del Marco
AbstractPrototype, wavelet-based lossy compression algorithms will be developed, for compression of both transient and narrowband sonar signals. An appropriate wavelet-related signal energy into the transform will be designed, with the goal of optimally concentrating 1 fewest number of coefficients. Standard 2-band wavelets will be examined, as well as M-band wavelets (M>2), wavelet-packets, and general perfect reconstruction multirate filterbanks. The family of Aware-developed translation-invariant wavelet transforms will also be examined as a possibility. A bit allocation strategy will be developed, tuned to the particular characteristics of the sonar data to be compressed. Standard entropy coding will be implemented to reduce the remaining redundancy. Zero-run length, and Huffman coding will be implemented. A compression/decompression performance analysis will be performed, to determine the bandwidth savings provided by the compression algorithm. The effects of lossy compression on data quality will also be investigated. Distortions introduced by compression will be evaluated both quantitatively and subjectively. Computational algorithm complexity will be explored, and potential processing bottlenecks will be identified. A final report will be written, documenting the compression algorithm and detailing numerical results of the performance analysis.
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