With the three-dimensional (3D) coordinates of objects captured by a sequence of images taken in different views, object reconstruction is a technique which aims to recover the shape and appearance information of objects. Although great progress in object reconstruction has been made over the past few years, object reconstruction in occlusion situations remains a challenging problem. In this paper, we propose a novel method to reconstruct occluded objects based on synthetic aperture imaging. Unlike most existing methods, which either assume that there is no occlusion in the scene or remove the occlusion from the reconstructed result, our method uses the characteristics of synthetic aperture imaging that can effectively reduce the influence of occlusion to reconstruct the scene with occlusion. The proposed method labels occlusion pixels according to variance and reconstructs the 3D point cloud based on synthetic aperture imaging. Accuracies of the point cloud are tested by calculating the spatial difference between occlusion and non-occlusion conditions. The experiment results show that the proposed method can handle the occluded situation well and demonstrates a promising performance.
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http://dx.doi.org/10.3390/s19030607 | DOI Listing |
Sci Rep
January 2025
School of Transportation and Geometics Engineering, Yangling Vocational & Technical College, Yangling, 712100, Shaanxi, China.
This work aims to improve the accuracy and efficiency of flood disaster monitoring, including monitoring before, during, and after the flood, to achieve accurate extraction of flood disaster change information. A modified U-Net network model, incorporating the Transformer multi-head attention mechanism (TM), is developed specifically for the characteristics of Synthetic Aperture Radar (SAR) images. By integrating the TM, the model effectively prioritizes image regions relevant to flood disasters.
View Article and Find Full Text PDFUltrasonics
January 2025
The Center for Fast Ultrasound Imaging, Department of Health Technology. Technical University of Denmark, Ørsteds Plads Building 349, Lyngby, DK-2800, Denmark.
Non-invasive estimation of pressure differences using 2D synthetic aperture ultrasound imaging offers a precise, low-cost, and risk-free diagnostic tool. Unlike invasive techniques, this preserves natural blood flow and avoids the limitations of devices that occupy lumen space. This paper evaluates a previously published estimator, modified to incorporate Singular Value Decomposition (SVD) echo-cancellation, using data from ten healthy volunteers and one patient.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Satellite Application Division, Korea Aerospace Research Institute (KARI), Daejeon 34133, Republic of Korea.
For change detection in synthetic aperture radar (SAR) imagery, amplitude change detection (ACD) and coherent change detection (CCD) are widely employed. However, time-series SAR data often contain noise and variability introduced by system and environmental factors, requiring mitigation. Additionally, the stability of SAR signals is preserved when calibration accounts for temporal and environmental variations.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Oceanography and Spatial Information, China University of Petroleum East China-Qingdao Campus, Qingdao 266580, China.
Salt marsh vegetation in the Yellow River Delta, including (), (), and (), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electrical and Software Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.
The fusion of synthetic aperture radar (SAR) and optical satellite imagery poses significant challenges for ship detection due to the distinct characteristics and noise profiles of each modality. Optical imagery provides high-resolution information but struggles in adverse weather and low-light conditions, reducing its reliability for maritime applications. In contrast, SAR imagery excels in these scenarios but is prone to noise and clutter, complicating vessel detection.
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