Integer and combinatorial optimization
Integer and combinatorial optimization
Arithmetic coding for data compression
Communications of the ACM
Combinatorial optimization
Disjunctive programming: properties of the convex hull of feasible points
Discrete Applied Mathematics
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Convex Optimization
A novel approach to medical image compression
International Journal of Bioinformatics Research and Applications
The status of the P versus NP problem
Communications of the ACM - The Status of the P versus NP Problem
Identifying hierarchical structure in sequences: a linear-time algorithm
Journal of Artificial Intelligence Research
Generalized kraft inequality and arithmetic coding
IBM Journal of Research and Development
Fundamentals of Computerized Tomography: Image Reconstruction from Projections
Fundamentals of Computerized Tomography: Image Reconstruction from Projections
Level embedded medical image compression based on value of interest
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Grammar-based codes: a new class of universal lossless source codes
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Universal lossless compression via multilevel pattern matching
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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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.