In video background modeling, ghosting occurs when an object that belongs to the background is assigned to the foreground. In the context of Principal Component Pursuit, this usually occurs when a moving object occludes a high contrast background object, a moving object suddenly stops, or a stationary object suddenly starts moving.

Based on a previously developed incremental PCP method, we propose a novel algorithm that uses two simultaneous background estimates based on observations over the previous n₁ and n₂ (n₁ n₂) frames in order to identify and diminish the ghosting effect. Our computational results show that the proposed method greatly improves both the subjective quality and accuracy as determined by the F-measure.