A New Image Fusion Method for ERT-EMT Dual-Modality System Used in Gas–Liquid–Solid Three-Phase Fluidized Bed

The electrical resistance tomography and electromagnetic tomography (ERT-EMT) dual-modality system can be used to reconstruct the image of cross-sectional three-phase distribution for gas–liquid–solid fluidized bed by fusing the reconstructed images of ERT and EMT. However, due to the small size of solid particles, the complexity of fluidization process, and the inconsistency of media distribution recognized by ERT and EMT, the existing fusion algorithms of dual-modality electrical tomography, which either divide the media distribution into binary distribution or use the consistency of the media distribution to be recognized to improve the image quality, are not applicable. Aiming at the problem, a new image fusion method based on guided image filtering (GIF) and image statistics is proposed in this article. First, the GIF method is used to decompose the images of ERT and EMT into base layers containing large-scale variations in intensity and detail layers with small-scale details. Then, the weights corresponding to the base layers and detail layers are calculated with the image statistics method and the GIF method, respectively. Through the process, the useful information in the reconstructed images of ERT and EMT is fully utilized. The simulation and experimental results demonstrate that the proposed fusion method can accurately reconstruct the gas–liquid–solid distribution.