WANG H X. Electrical tomography[M]. 1st ed. Beijing: Science Press, 2013: 33–35. (in Chinese)

Google Scholar 

LI A Q, MENG S, HUANG K, et al. On the concentration models in electrical capacitance tomography for gas-fluidized bed measurements[J]. Chemical engineering journal, 2022, 435: 134989.

Article  Google Scholar 

LIU J, LIU S, SUN S, et al. Internal structure visualization of flow and flame by process tomography and PLIF data fusion[J]. Journal of thermal science, 2018, 27(1): 64–73.

Article  ADS  Google Scholar 

CARCANGIU S, FANNI A, MONTISCI A. Electric capacitance tomography for nondestructive testing of standing trees[J]. International journal of numerical modelling: lectronic networks, devices and fields, 2019, 32(4): e2252.

Article  Google Scholar 

ZHAO Y L, GUO B L, YAN Y Y. Research progress and analysis of electrical capacitance tomography[J]. Chinese journal of scientific instrument, 2012, 8: 1909–1920. (in Chinese)

Google Scholar 

ZHAO J W, YUAN Q P, QIN J, et al. Single image super-resolution reconstruction using multiple dictionaries and improved iterative back-projection[J]. Optoelectronics letters, 2019, 15(2): 156–160.

Article  ADS  Google Scholar 

WANG H X, TANG L, YAN Y. Total variation regularization algorithm for electrical capacitance tomography image reconstruction[J]. Chinese journal of scientific instrument, 2007, 28(11): 2014–2018. (in Chinese)

Google Scholar 

HUANG D T, HUANG W Q, HUANG H, et al. Application of regularization technique in image super-resolution algorithm via sparse representation[J]. Optoelectronics letters, 2017, 13(6): 439–443.

Article  ADS  Google Scholar 

YAN C M, MU Z, ZHANG D L, et al. ECT image reconstruction based on improved Landweber algorithm[J]. Chinese journal of sensors and actuators, 2019, 32(10): 1522–1526. (in Chinese)

Google Scholar 

TIAN Z N, GAO X X, QIU L M, et al. Experimental imaging and algorithm optimization based on deep neural network for electrical capacitance tomography for LN2-VN2 flow[J]. Cryogenics, 2022, 127: 103568.

Article  Google Scholar 

TONG G W, LIU S, LIU S. Computationally efficient image reconstruction algorithm for electrical capacitance tomography[J]. Transactions of the institute of measurement & control, 2019, 41(3): 631–646.

Article  ADS  Google Scholar 

LIU J, LIU S, ZHOU W, et al. Flame detection on swirl burner using ECT with dynamic reconstruction algorithm based on the split Bregman iteration[J]. IEEE sensors journal, 2017, 17(22): 7290–7297.

Article  ADS  Google Scholar 

CUI L, TIAN P, WANG C, et al. Iterative weighted fidelity and hybrid regularization-based algorithm for ECT[J]. Measurement science and technology, 2022, 33(6): 065404.

Article  ADS  Google Scholar 

CUI A, PENG J, LI H, et al. Iterative thresholding algorithm based on non-convex method for modified LP-norm regularization minimization[J]. Journal of computational and applied mathematics, 2019, 347: 173–180.

Article  MathSciNet  MATH  Google Scholar 

ZHAO Q, LIU S, CHAI X, et al. A novel computational imaging algorithm based on split Bregman iterative for electrical capacitance tomography[J]. Measurement science and technology, 2021, 32(12): 125401.

Article  ADS  Google Scholar 

LUO Y H. Research on exponential filter in filtered back projection algorithm for CT image reconstruction[J]. Computer science, 2014, 101: 220–223.

Google Scholar 

YAN C M, MU Z. An improved gradient accelerated Landweber algorithm and its application in ECT image reconstruction[J]. Journal of electronic measurement and instrument, 2021, 35(6): 169–175.

ADS  Google Scholar