부산대학교 도서관

In recent years, multibaseline phase unwrapping (MBPU) has been widely studied, but it is still suffering from the problem of low noise robustness. In view of this, two cluster correction methods for the cluster analysis-based MBPU algorithms are presented to improve the accuracy and effectiveness of the algorithm. In the first method, a suitable box centered on each pixel is selected and the cluster with the highest frequency in the box is taken as the corrected cluster to which the central pixel belongs; in the second method, all pixels are divided into core pixels and noncore pixels according to the predefined density, and then the cluster of the noncore pixels is corrected to the one that appears most frequently in the selected box centered on the noncore pixels. Experiments on both simulated and real datasets confirm the effectiveness of the proposed cluster correction methods.