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Remote sensing image dehazing using a wavelet-based generative adversarial networks.
Sci Rep
January 2025
College of Electrical and Information Engineering, Beihua University, Jilin, 132013, China.
Remote sensing images often suffer from the degradation effects of atmospheric haze, which can significantly impair the quality and utility of the acquired data. A novel dehazing method leveraging generative adversarial networks is proposed to address this challenge. It integrates a generator network, designed to enhance the clarity and detail of hazy images, with a discriminator network that distinguishes between dehazed and real clear images.
View Article and Find Full Text PDFA synergetic approach for multidimensional drought assessment in the Indian agro-climatic zone using coherency, propagation and AHP techniques.
Environ Sci Pollut Res Int
January 2025
Department of Agricultural Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India.
Drought is one of the most detrimental natural calamities to the economy. Despite its significant consequences, the evolution from meteorological to agricultural and hydrological droughts still needs to be explored. A thorough investigation was carried out in India's eastern hills and plateau region to determine the extent of drought's impact through indices.
View Article and Find Full Text PDFNonlinear Harmonics: A Gateway to Enhanced Image Contrast and Material Discrimination.
Adv Sci (Weinh)
January 2025
School of Engineering, Ulster University, York Street, Belfast, Northern Ireland, BT15 1AP, UK.
Recent advancements in atomic force microscopy (AFM) have enabled detailed exploration of materials at the molecular and atomic levels. These developments, however, pose a challenge: the data generated by microscopic and spectroscopic experiments are increasing rapidly in both size and complexity. Extracting meaningful physical insights from these datasets is challenging, particularly for multilayer heterogeneous nanoscale structures.
View Article and Find Full Text PDFLensless imaging offers a lightweight, compact alternative to traditional lens-based systems, ideal for exploration in space-constrained environments. However, the absence of a focusing lens and limited lighting in such environments often results in low-light conditions, where the measurements suffer from complex noise interference due to insufficient capture of photons. This study presents a robust reconstruction method for high-quality imaging in low-light scenarios, employing two complementary perspectives: model-driven and data-driven.
View Article and Find Full Text PDFNoise-Tolerant Force Calculations in Density Functional Theory: A Surface Integral Approach for Wavelet-Based Methods.
J Phys Chem A
January 2025
Hylleraas Centre, Department of Chemistry, UiT the Arctic University of Norway, Tromso̷ N-9037, Norway.
We introduce a method for computing quantum mechanical forces through surface integrals over the stress tensor within the framework of the density functional theory. This approach avoids the inaccuracies of traditional force calculations using the Hellmann-Feynman theorem when applied to multiresolution wavelet representations of orbitals. By integrating the quantum mechanical stress tensor over surfaces that enclose individual nuclei, we achieve highly accurate forces that exhibit superior consistency with the potential energy surface.
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