Search Results for "compression"
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Showing 5 open source projects for "compression"
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export_fig
A MATLAB toolbox for exporting publication quality figures
export_fig is a MATLAB toolbox designed to simplify high-quality figure export from MATLAB, faithfully preserving visual appearance as seen on-screen—including size, colours, fonts, and layout—while offering precise control over output formats such as PNG, PDF, EPS, and more. Exporting a figure from MATLAB the way you want it (hopefully the way it looks on screen), can be a real headache for the unitiated, thanks to all the settings that are required, and also due to some eccentricities... -
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Enhanced SAR Compression
VOP Algorithm with improved speed and compression
This work is described in: Orzada S, Fielder TM, Quick HH, Ladd ME, "A local SAR compression algorithm with improved compression, speed and flexibility", https://doi.org/10.1002/mrm.28739. This new algorithm is an iterative expansion of the exisisting local SAR compression algorithm for MRI proposed by Lee et al. ( https://doi.org/10.1002/mrm.23140) The number of VOPs is approximately halved with the new algorithm, while at the same time the compression time is reduced with speed-up factors of up to 2.5. -
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VOP post-processing
Post-processing algorithms for SAR compression
Here we introduce to algorithms for post-processing of VOP sets. Algorithm 1 reduces the Overestimation for a given set of VOPs. Especially useful to reduce the overestimation in VOP sets calculated with the compression algorithms by Lee et al. and Orzada et al. Algorithm 2 tests a given set of VOPs for redundancy. It can be used to reduce the number of VOPs in a dataset produced by Eichfelder and Gebhardt's algorithm. Especially useful when you have a vendor provided VOP set only. -
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Relative Overestimation VOP
VOP compression for MRI with overestimation control
**** This work is outdated! For better compression and speed use these: ***** https://sourceforge.net/projects/enhanced-sar-compression/ Virtual Observation Points SAR compression. Contains multiple Algorithms: Compression according to Eichfelder et al. and Lee et al. The Lee algorithm is enhanced by including overestimation control to reduce maximum relative overestimation. -
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CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.
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