Zamani, M;
Bayford, R;
Demosthenous, A;
(2020)
Adaptive Electrical Impedance Tomography Resolution Enhancement Using Statistically Quantized Projected Image Sub-Bands.
IEEE Access
, 8
pp. 99797-99805.
10.1109/access.2020.2996500.
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Abstract
This paper proposes an adaptive image enhancement method for electrical impedance tomography (EIT). The images are enhanced based on a steerable and multi-scale resolution enhancement algorithm. It is initiated by capturing the spatial variations in decomposition orientations, and decomposition scales of the EIT image. The interpretation of projected image sub-bands is translated into resolution through statistical processes. A steerable filter containing Gaussian basis function derivatives captures the statistical information. Using the regional quantization method (RQM) proposed in this paper, projection weights are computed through spatial statistics of the image sub-bands and tuned adaptively. RQM assigns more resolution to those directional edges which have higher standard deviation and embeds high-order curvatures into the EIT images while suppressing noise. Comparison with conventional image enhancement methods demonstrates the superior performance of RQM. Using RQM it is shown that for 16, 32 and 64 electrode configurations with noise-free recording of 32×32 EIT images the number of electrodes can be reduced by 5, 7 and 12 respectively without loss of detail.
| Type: | Article |
|---|---|
| Title: | Adaptive Electrical Impedance Tomography Resolution Enhancement Using Statistically Quantized Projected Image Sub-Bands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/access.2020.2996500 |
| Publisher version: | https://doi.org/10.1109/access.2020.2996500 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Adaptive resolution enhancement, contrast improving index, distortion embedding, electrical impedance tomography, electrodes optimization, local statistics, signal-to-noise ratio, steerable filter |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10100058 |
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