Title :
Sparse representation in electrical resistance tomography based on extended sensitivity matrix
Author :
Jiamin Ye ; Haigang Wang ; Guizhi Qiu ; Wuqiang Yang
Author_Institution :
Inst. of Eng. Thermophys., Beijing, China
Abstract :
Electrical resistance tomography is a soft-field tomography technique, i.e. the electrical field is changed everywhere in the sensing area with the change of conductivity in any pixel. To improve the image quality, an extended sensitivity matrix is designed in this paper. The base conductivity elements in the extended sensitivity matrix are consisted of a series of blocks with different number of pixels at all possible locations in the sensing region. Based on the new sensitivity matrix, a sparse representation method is implemented to reconstruct the conductivity distribution of cross-sectional area. Simulation results show that the proposed method based on the extended sensitivity matrix can reconstruct the image with a high quality.
Keywords :
image reconstruction; image representation; matrix algebra; tomography; base conductivity elements; conductivity distribution reconstruction; cross-sectional area; electrical resistance tomography; extended sensitivity matrix; image quality improvement; image reconstruction; soft-field tomography technique; sparse representation method; Conductivity; Electrodes; Image reconstruction; Sensitivity; Sensors; Sparse matrices; Tomography; electrical resistance tomography; image reconstruction; resistance sensor;
Conference_Titel :
Imaging Systems and Techniques (IST), 2014 IEEE International Conference on
Conference_Location :
Santorini
DOI :
10.1109/IST.2014.6958443