Increasing the lucidity of sandstorm images using a multistep color reparation algorithm.

Sandstorms pose a substantial hurdle to image clearness, affecting visibility, detail representation, and color quality. In this study, a novel algorithm named multistep color reparation (MCR) is constructed, particularly for the enhancement of images impacted by sandstorms. MCR includes a thorough procedure comprising five distinct phases. The first phase focuses on enhancing color indemnity by effectively compensating the missing color information, assuring that the enhanced images appear with better true-to-life colors. Next, a statistics-based intensity redistribution is employed as a second phase to emphasize tonality, ensuring better perceptual quality. The third phase applies an optimized intuitionistic fuzzy model, leveraging the fuzzy model's undiscovered abilities to remove the dust veil. Following this, a color deviation correction phase is executed to rectify the emerging color shifts and inaccuracies, applying corrective measures to enliven accurate color representation. Finally, a fast visibility restoration approach is implemented to improve the visibility and provide better saturation. To evaluate the efficacy of MCR, thorough experiments were performed comparing it with eight state-of-the-art algorithms. Quality assessments were carried out using six high-level image evaluation metrics alongside the processing times. The findings exhibited that MCR outperforms all competing algorithms, and it efficaciously addressed the challenges posed by sandstorm-induced degradation, presenting substantial enhancements in perceptual fidelity and quality. [ABSTRACT FROM AUTHOR]