Enhancing the quality of tomographic image by means of image reconstruction based on hybrid grids

Tomography is an important technique for ionosphere investigation. For a voxel-based tomography method, the way the voxel model is constructed is crucial and may affect the quality of the reconstructed image. However, previous research has paid less attention to voxel model construction and how this may improve or reduce the quality of the produced tomography image. To mitigate this issue, a new method is proposed named Image Reconstruction based on Hybrid Grids (IRHG). In IRHG, two hybrid grid models, each with a top and a bottom component (separated by a splitting height) that have different voxel resolution configurations, are adopted for tomographic inversions. Thereafter, the advantageous components of the two reconstructed images are combined to produce a new image (i.e., the image for IRHG). Initial testing showed that a slight improvement was achieved when compared to a uniformly spaced voxel model. This was further enhanced by changing the splitting height to 400 km and the use of different vertical and horizontal voxel resolutions. Finally, an improvement in root mean square error (RMSE) and mean absolute error (MAE) of 28.24% and 23.24% (for quiet ionosphere days), and 5.96% and 9.01% (for disturbed days) respectively, were achieved. The IRHG method is supposed to be independent of the inversion algorithm, e.g., the improved algebraic reconstruction technique (IART) used in this paper, and promises to hold benefits for other algorithms, which may together improve the reconstructed tomographic image.