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Discrete Tomography Data Footprint Reduction via Natural Compression

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In Discrete Tomography (DT) by electron microscopy, 2-D projection images are acquired from various angles, by tilting the sample, generating new challenges associated with the problem of formation, acquisition, compression, transmission, and analysis of enormous quantity of data. Data Footprint Reduction (DFR) is the process of employing one or more techniques to store a given set of data in less storage space. Modern lossless compressors use classical probabilistic models only, and are unable to match high end application requirements like “Arbitrary Bit Depth” (ABD) resolution and information “Dynamic Upscale Regeneration” (DUR). Traditional \mathbbQ Arithmetic can be regarded as a highly sophisticated open logic, powerful and flexible bidirectional (LTR and RTL) formal language of languages, according to brand new “Information Conservation Theory” (ICT). This new awareness can offer competitive approach to guide more convenient algorithm development and application for combinatorial lossless compression, we named “Natural Compression” (NC). To check practical implementation performance, a first raw example is presented, benchmarked to standard, more sophisticate lossless JPEG2000 algorithm, and critically discussed. NC raw overall lossless compression performance compare quite well to standard one, but offering true ABD and DUR at no extra computational cost.
Wydawca
Rocznik
Strony
273--284
Opis fizyczny
Bibliogr. 57 poz., fot., wykr.
Twórcy
  • Dipartimento di Bioingegneria, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133 Milano, Italy
  • Dipartimento di Bioingegneria, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133 Milano, Italy
autor
  • Dipartimento di Bioingegneria, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133 Milano, Italy
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fe4e6ec6-5802-41f3-95b6-c45b01e92bfd
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