Weighted Schatten p-norm and Laplacian scale mixture-based low-rank and sparse decomposition for foreground–background separation
Ruibo Fan, Mingli Jing, Lan Li, Jingang Shi, Yufeng Wei · Journal of Electronic Imaging · 2023
Low-rank and sparse decomposition (LRSD) plays a vital role in foreground–background separation. The existing LRSD methods have the drawback: imprecise surrogate functions of rank and sparsity. We propose the weighted Schatten p-norm (WSN) and Laplacian scale mixture (LSM) method based on LRSD for foreground–background separation, which introduces the WSN and LSM to improve this drawback. To demonstrate the performance of the proposed method, it is applied to foreground–background separation and gets the highest average F-measure score.