Showing 5 open source projects for "compressive sensing"

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  • 1

    pyL1min

    General purpose norm-1 minimization solver in Python

    ...It is based on NumPy/SciPy, CVXOPT ( FFTW enabled) to solve l1 minimization problems that are based on interior point methods. You need to install Python, NumPy/SciPy and CVXOPT ( FFTW enabled) to use this software. The test.py program demonstrates a simple application in Compressive Sensing and shows how to use l1min module. You need to install matplotlib to plot diagrams. Note: pyL1min can handle complex as well as real vectors.
    Downloads: 0 This Week
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  • 2

    KL1p

    A portable C++ library for Compressed Sensing

    KL1p is a portable C++ framework for handling sparse recovery of inverse problems of underdetermined linear systems, like in compressed sensing technique.
    Downloads: 6 This Week
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  • 3

    DCTV

    DUAL CONSTRAINED TV-BASED REGULARIZATION ON GRAPHS

    Algorithms based on Total Variation (TV) minimization are prevalent in image processing. They play a key role in a variety of applications such as image denoising, compressive sensing and inverse problems in general. In this work, we extend the TV dual framework that includes Chambolle's and Gilboa-Osher's projection algorithms for TV minimization. We use a flexible graph data representation that allows us to generalize the constraint on the projection variable. We show how this new formulation of the TV problem may be solved by means of fast parallel proximal algorithms. ...
    Downloads: 0 This Week
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  • 4

    OpenRecon

    OpenRecon is an open-source software library for image reconstruction.

    Moved to https://bitbucket.org/bid/openrecon
    Downloads: 0 This Week
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  • 5

    Enabling Green Video Streaming over IoT

    Enabling Green Video Streaming Over Internet of Things

    ...Its prime objective is to enable video streaming as part of the realization of IoT with reduced overall ecological footprint, in terms of energy consumption and CO2 emissions, while maintaining video fidelity as tradeoff with the energy and carbon footprints. The solution consists of a new novel architecture for IoM and a framework that comprises of compressive sensing based video encoding and communication protocols for green communication. IEEE 802.11 is enhanced for new power saving functions to exploit it as the link layer providing high data rate at low power for multimedia devices.
    Downloads: 0 This Week
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