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<title><![CDATA[Compressive Sensing Approach with Double Layer Soft Threshold for ECVT Static Imaging]]></title>
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<name type="Personal Name" authority="">
<namePart>Nur Afny Catur Andriyani</namePart>
<role><roleTerm type="text">Pengarang</roleTerm></role>
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<publisher><![CDATA[Universitas Diponogoro]]></publisher>
<dateIssued><![CDATA[2020]]></dateIssued>
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<languageTerm type="text"><![CDATA[English]]></languageTerm>
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<note>Electrical Capacitance Volume Tomography
(ECVT) is a capacitance based tomography technology which is
developed since its advantages on non-invasive properties, low
energy, and portability. One of the challenge on developing this
tomography technology is on its imaging algorithm. Naturally the
imaging method forms under-determined linear system which is
indicated by dimension of the measurement is much smaller
compared to the projected value dimension. Mathematically it
implies ill-posed inverse problem. Therefore Compressive Sensing
framework is used to solve the corresponding inverse problem. To
improve the accuracy of the predicted image reconstruction, new
threshold approach, Double Layer Soft Threshold, is proposed
and attached to the proposed Compressive Sensing based ECVT
imaging method. The simulations results show that the proposed
method is able to improve the conventional ECVT imaging
method, Iterative Linear Back Projection (ILBP), by significantly
eliminating the elongation error.</note>
<subject authority=""><topic><![CDATA[Compressive Sensing]]></topic></subject>
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