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• W1489623746 abstract "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 $mathbb{Q}$ 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." @default.
• W1489623746 created "2016-06-24" @default.
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• W1489623746 date "2013-01-01" @default.
• W1489623746 modified "2023-09-27" @default.
• W1489623746 title "Discrete Tomography Data Footprint Reduction via Natural Compression" @default.
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• W1489623746 doi "https://doi.org/10.3233/fi-2013-864" @default.
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