The satellite jitter effect observable in the digital elevation model of difference, herein referred to as DoD, generated using tri-stereo pairs of Pléiades images is a common phenomenon that can reduce the precision of elevation measurements making it challenging for 3D change detection in the land surface. To address this issue, previous studies used correction methods based on polynomial and sinusoid fitting to reduce the jitter effect. However, such approaches do not entirely remove these undulations. In this paper, the image noise reduction task is framed as a signal filtering problem, to eliminate these repetitive patterns while preserving relevant information for accurate change detection using Fourier transform. The noise frequency is identified through the frequency spectrum using a threshold-based method, allowing the subsequent application of a finite impulse response filter to remove the noise. Experiments conducted on Pléiades DoDs data covering the Lebna watershed located in the north of Tunisia validate the effectiveness of this approach. The results demonstrate that the Fourier transform-based filtering method significantly outperforms the state-of-the-art methods, both in terms of qualitative visual assessment and quantitative performance metrics.