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

Abstract

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 article presents a consistency preserved scattering model designed with multiple features to remove haze and thin cloud effects. Specifically, three modules named ellipsoid scattering distribution (ESD), illumination linear mapping (ILM), and spectral proportion combination (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.

Keywords

• Cross-patch consistency
• haze and thin cloud removal
• illumination distribution estimation
• nonuniform scattering