Back-projection Filtration Image Reconstruction Approach for Reducing Out-of-plane Artifacts in Laminography

Because of incomplete depth information in computed laminography, 3D reconstructed images are contaminated by out-of-plane artifacts, or ripple artifacts along the depth direction. Furthermore, these issues become more severe whenever printed circuit boards (PCB) are imaged due to the presence of high density materials, such as ball grid array, chips, etc. In this reasearch, in order to remove these artifacts, we proposed the use of the voting strategy. This method is a weighted back-projection which gives less weight to outliers, or odd values. However, standard analytical reconstruction methods, such as filtered back-projection (FBP), cannot fully judge and remove the outliers. Thus, we proposed to combine this strategy with the back-projection filtration (BPF) reconstruction method, which first reconstructs the derivative of the projection image, and then filters the reconstructed image by the Hilbert transform. Ripple artifacts were shown to have been dramatically reduced by using the voting strategy in the BPF algorithm.