TY - JOUR A2 - Gupta, Punit AU - Yang, Zhao AU - Wan, Jixin PY - 2022 DA - 2022/06/23 TI - A Threshold Segmentation Algorithm for Sculpture Images Based on Sparse Decomposition SP - 8523370 VL - 2022 AB - Aiming at the problem of low efficiency and insufficient accuracy of threshold solution in multithreshold sculpture image segmentation, this paper proposes a threshold segmentation algorithm for sculpture images based on sparse decomposition. In this paper, sparse decomposition is introduced to optimize the model to reduce the impact of local noise on segmentation accuracy, and an energy functional based on pixel coconstraint is built to make up for the defect that pixels cannot retain local details. At the same time, the weighted sum of elite solution sets is used to determine Neighborhood centers increase communication between groups. Experiments show that compared with other algorithms, the above method has significant advantages in convergence efficiency and accuracy. SN - 1024-123X UR - https://doi.org/10.1155/2022/8523370 DO - 10.1155/2022/8523370 JF - Mathematical Problems in Engineering PB - Hindawi KW - ER -