Consistency Preserved Nonuniform Scattering Removal for Wide-Swath Remote Sensing Images

Removal of haze and thin clouds in remote sensing images has been extensively studied, leading to the development of effective methods. However, when applied to wide-swath images, conventional dehazing approaches often generate patch-level inconsistencies during combination. To address the issue, this paper presents a consistency preserved scattering model designed with multiple features to remove haze and thin cloud effects. Specifically, three modules named ESD, ILM and SPC are introduced to improve the basic prior-based dehazing method. ESD focuses on cloud area exclusion to ensure accurate estimation with the scattering distribution map. ILM is based on the linear relationship with scattering distribution and illumination, aiming to smooth the global illumination. SPC addresses the spectral adaptation issues in wide-swath scenes. Experimental results indicate that, compared to state-of-the-art methods, the proposed model and method effectively restores textural details in remote sensing imagery affected by heterogeneous haze, while resolving cross-patch inconsistency to enhance overall image coherence and interpretability.