An Adjacent Differential Statistics Method for IRFPA Nonuniformity Correction

In this paper, a novel scene-based nonuniformity correction (SBNUC) method using statistics between adjacent detectors for infrared focal-plane array (IRFPA) is proposed. Differential operation is designed as a decorrelation process to minimize the scene information remained into the nonuniformity parameters updating. Then, a global transfer matrix is established to construct the nonuniformity compensation matrix for the entire image. The adjacent differential statistics are demonstrated to be more effective and sufficient to estimate the nonuniformity when temporal variation is lacking. In addition, the proposed method exhibits the more superior capability of converging and does better in correcting all spatial components of nonuniformity. Application in simulated imagery and real infrared image shows the proposed method's excellent performance in convergence and elimination of ghosting artifacts.