{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-1470"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-1470","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"New methods in image compression using multi-level transforms and adaptive statistical encoDing","abstract":"The need to meet the demand for high quality digital images, with comparatively modest storage requirements, is driving the development of new image compression techniques. This demand has spurred new techniques based on time to frequency spatial transformation methods. At the core of these methods are a family of transformations built on basis sets called \"wavelets.\" The wavelet transform permits an image to be represented in a substantially reduced space by transferring the energy of the image to a smaller set of coefficients. 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