Ultra-high-definition (UHD) image restoration faces significant challenges due to its high resolution, complex content, and intricate details. To cope with these challenges, we analyze the restoration process in depth through a progressive spectral perspective, and deconstruct the complex UHD restoration problem into three progressive stages: zero-frequency enhancement, low-frequency restoration, and high-frequency refinement. Building on this insight, we propose a novel framework, ERR, which comprises three collaborative sub-networks: the zero-frequency enhancer (ZFE), the low-frequency restorer (LFR), and the high-frequency refiner (HFR). Specifically, the ZFE integrates global priors to learn global mapping, while the LFR restores low-frequency information, emphasizing reconstruction of coarse-grained content. Finally, the HFR employs our designed frequency-windowed kolmogorov-arnold networks (FW-KAN) to refine textures and details, producing high-quality image restoration. Our approach significantly outperforms previous UHD methods across various tasks, with extensive ablation studies validating the effectiveness of each component. The code is available at here.

Phase filtering is one of the core signal processing steps in interferometric synthetic aperture radar (InSAR). In recent years, InSAR phase filtering algorithms have evolved from traditional solutions to deep learning (DL) methods, significantly improving the processing efficiency. However, most DL-based phase filtering techniques originate from optical filtering methods, and these methods inevitably entail a tradeoff between noise suppression and detail preservation. To resolve this contradiction and fully take into account the characteristics of InSAR phase, a multiscale phase filtering network (MPFNet) based on multilook information fusion is proposed. First, the network adopts the multiscale structure to balance noise suppression and detail preservation, where the multiscale information is obtained through multilook interferograms of varying numbers of looks. Second, drawing on the mechanism of super-resolution, the network incorporates the residual feature distillation blocks (RFDBs) to restore the scale of interferograms. Finally, in response to the demand for complex phase filtering, a loss function based on cosine similarity is constructed, which avoids the discontinuity at$\pm \pi $affecting the filtering results. Computer simulation and experiments based on real InSAR data verified the effectiveness of the proposed method.

With the rapid development of modern science and technology, on the basis of 5g background, satellite communication technology has been more and more applied because of its unique advantages, and is developing towards multi band, multi polarization and broadband access. In today's 5g era, the structural design method and the analysis of the model design of the large truss satellite communication antenna frame are briefly introduced to him. The structural design and model design mainly include the driving device of the main components and the accuracy calculation of the shafting. In addition to optimizing the structure of antenna main frame and synchronizer, the final element method is applied to the actual mechanical calculation and analysis of antenna structure model, which can better ensure the accuracy of antenna to a certain extent. Enjoy the wind speed of your work speed. After the antenna has been working for a long time, all kinds of data generated in the working process can show that the structural characteristics of the antenna frame are better than the optimized structural requirements. This paper discusses the structure design method and model design analysis of satellite communication antenna based on 5g background, hoping to promote the development and progress of related research.

with the support of the Science and Technology Research Project Fund (JJKH20190974KJ) of Jilin Provincial Education Department and relying on the Jilin Province Digital Agriculture Key Discipline, the key technologies of autonomous cruise system for farmland environment information collection are studied in depth in this paper. This paper describes the whole frame structure of the autonomous cruise system, the closed-loop control structure of the hardware system, the control flow of the software system and the debugging flow of the cruise system. The whole system runs stably, which provides a reference scheme for the popularization and application of digital agriculture.