Optical and synthetic aperture radar (SAR) images exhibit non-negligible intensity differences due to their unique imaging mechanisms, which makes it difficult for classical SIFT-based algorithms to obtain sufficiently correct correspondences when processing the registration of these two types of images. To tackle this problem, an accurate optical and SAR image registration algorithm based on the SIFT algorithm (OS-PSO) is proposed. First, a modified ratio of exponentially weighted averages (MROEWA) operator is introduced to resolve the sudden dark patches in SAR images, thus generating more consistent gradients between optical and SAR images. Next, we innovatively construct the Harris scale space to replace the traditional difference in the Gaussian (DoG) scale space, identify repeatable key-points by searching for local maxima, and perform localization refinement on the identified key-points to improve their accuracy. Immediately after that, the gradient location orientation histogram (GLOH) method is adopted to construct the feature descriptors. Finally, we propose an enhanced matching method. The transformed relation is obtained in the initial matching stage using the nearest neighbor distance ratio (NNDR) and fast sample consensus (FSC) methods. And the re-matching takes into account the location, scale, and main direction of key-points to increase the number of correctly corresponding points. The proposed OS-PSO algorithm has been implemented on the Gaofen and Sentinel series with excellent results. The superior performance of the designed registration system can also be applied in complex scenarios, including urban, suburban, river, farmland, and lake areas, with more efficiency and accuracy than the state-of-the-art methods based on the WHU-OPT-SAR dataset and the BISTU-OPT-SAR dataset.

In this paper, we developed a paper-based fluorescent sensor using functional composite materials composed of graphene quantum dots (GQDs) coated with molecularly imprinted polymers (MIPs) for the selective detection of tetracycline (TC) in water. GQDs, as eco-friendly fluorophores, were chemically grafted onto the surface of paper fibers. MIPs, serving as the recognition element, were then wrapped around the GQDs via precipitation polymerization using 3-aminopropyltriethoxysilane (APTES) as the functional monomer. Optimal parameters such as quantum dot concentration, grafting time, and elution time were examined to assess the sensor’s detection performance. The results revealed that the sensor exhibited a linear response to TC concentrations in the range of 1 to 40 µmol/L, with a limit of detection (LOD) of 0.87 µmol/L. When applied to spiked detection in actual water samples, recoveries ranged from 103.3% to 109.4%. Overall, this paper-based fluorescent sensor (MIPs@GQDs@PAD) shows great potential for portable, multi-channel, and rapid detection of TC in water samples in the future.