PDE-based deghosting algorithm for correction of nonuniformity in infrared focal plane array
基于PDE去鬼影的自适应非均匀性校正算法研究

Generally, most of adaptive nonuniformity correction algorithms have the ghosting artifact problem. In this paper, the cause of ghosting artifacts in Neural Network nonuniformity correction (NN-NUC) algorithm for infrared focal plane array (IRFPA) was studied. Based on the analysis, a novel algorithm for eliminating the ghosting artifact was proposed, which replaces the linear spatial average filter in the NN-NUC algorithm with the partial differential equation (PDE)-based nonlinear filter to estimate the desired image. The comparison experiment using real IRFPA infrared image shows that the proposed algorithm can effectively remove the ghosting artifact. Compared with several deghosting algorithms, the proposed algorithm converges much faster.