Non-uniform sparse scanning angle selection method for limited angle industrial CT detection of laminated cells

Laminated cells can be rapidly scanned using sparse angle computed tomography (CT), but the traditional uniform sparse scanning method fails to adequately capture internal structural differences, leading to missing structures in the reconstructed image. To address this issue, we introduce a scanning method—a non-uniform sparse scanning angle selection method for limited angle industrial CT detection of laminated cells. First, the spectrum distribution map is generated by applying Fourier transform to the projection data. A threshold is established by taking the average of frequency amplitudes. Next, the number of frequency categories with amplitudes exceeding the threshold is counted to select a suitable limited angle range. Then, the non-uniform sparse scanning angles within the limited angle range are determined based on the singularity distribution curve in the projection domain. This scanning method ensures that more relevant data is collected while avoiding the data redundancy. Finally, the effectiveness of the proposed method is verified through numerical simulation and actual scanning experiments. In comparison with the latest scanning angle selection methods, our method collects more data and significantly improves image reconstruction quality while maintaining the same number of scanning angles.