Block unshifting high-accuracy motion estimation: A new method adapted to super-resolution enhancement

2018 ◽  
Vol 65 ◽  
pp. 81-93
Author(s):  
Konstantinos Konstantoudakis ◽  
Lazaros Vrysis ◽  
Nikolaos Tsipas ◽  
Charalampos Dimoulas
1996 ◽  
Vol 176 ◽  
pp. 53-60 ◽  
Author(s):  
J.-F. Donati

In this paper, I will review the capabilities of magnetic imaging (also called Zeeman-Doppler imaging) to reconstruct spot distributions of surface fields from sets of rotationnally modulated Zeeman signatures in circularly polarised spectral lines. I will then outline a new method to measure small amplitude magnetic signals (typically 0.1% for cool active stars) with very high accuracy. Finally, I will present and comment new magnetic images reconstructed from data collected in 1993 December at the Anglo-Australian Telescope (AAT).


2012 ◽  
Vol 170-173 ◽  
pp. 2924-2928
Author(s):  
Sheng Biao Chen ◽  
Yun Zhi Tan

In order to measure the water drainage volume in soil mechanical tests accurately, it develop a new method which is based on principles of optics. And from both physical and mathematic aspects, it deduces the mathematic relationship between micro change in displacement and the increment projected on screen. The result shows that total reflection condition is better than refraction condition. What’s more, the screen could show the water volume micro variation clearly, so it can improve the accuracy of measurement.


Author(s):  
Yan Tian

AbstractIn this paper, we provide further illustrations of prolate interpolation and pseudospectral differentiation based on the barycentric perspectives. The convergence rates of the barycentric prolate interpolation and pseudospectral differentiation are derived. Furthermore, we propose the new preconditioner, which leads to the well-conditioned prolate collocation scheme. Numerical examples are included to show the high accuracy of the new method. We apply this approach to solve the second-order boundary value problem and Helmholtz problem.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Liliana Barbieri ◽  
Huw Colin-York ◽  
Kseniya Korobchevskaya ◽  
Di Li ◽  
Deanna L. Wolfson ◽  
...  

AbstractQuantifying small, rapidly evolving forces generated by cells is a major challenge for the understanding of biomechanics and mechanobiology in health and disease. Traction force microscopy remains one of the most broadly applied force probing technologies but typically restricts itself to slow events over seconds and micron-scale displacements. Here, we improve >2-fold spatially and >10-fold temporally the resolution of planar cellular force probing compared to its related conventional modalities by combining fast two-dimensional total internal reflection fluorescence super-resolution structured illumination microscopy and traction force microscopy. This live-cell 2D TIRF-SIM-TFM methodology offers a combination of spatio-temporal resolution enhancement relevant to forces on the nano- and sub-second scales, opening up new aspects of mechanobiology to analysis.


2021 ◽  
Vol 13 (9) ◽  
pp. 1854
Author(s):  
Syed Muhammad Arsalan Bashir ◽  
Yi Wang

This paper deals with detecting small objects in remote sensing images from satellites or any aerial vehicle by utilizing the concept of image super-resolution for image resolution enhancement using a deep-learning-based detection method. This paper provides a rationale for image super-resolution for small objects by improving the current super-resolution (SR) framework by incorporating a cyclic generative adversarial network (GAN) and residual feature aggregation (RFA) to improve detection performance. The novelty of the method is threefold: first, a framework is proposed, independent of the final object detector used in research, i.e., YOLOv3 could be replaced with Faster R-CNN or any object detector to perform object detection; second, a residual feature aggregation network was used in the generator, which significantly improved the detection performance as the RFA network detected complex features; and third, the whole network was transformed into a cyclic GAN. The image super-resolution cyclic GAN with RFA and YOLO as the detection network is termed as SRCGAN-RFA-YOLO, which is compared with the detection accuracies of other methods. Rigorous experiments on both satellite images and aerial images (ISPRS Potsdam, VAID, and Draper Satellite Image Chronology datasets) were performed, and the results showed that the detection performance increased by using super-resolution methods for spatial resolution enhancement; for an IoU of 0.10, AP of 0.7867 was achieved for a scale factor of 16.


2012 ◽  
Vol 178-181 ◽  
pp. 1250-1253
Author(s):  
Yu Hua Li ◽  
Kai Huang ◽  
Ying Zhen Gao

When we make design of mixture ratio, we always use normal equation method (NEM), but the solution value of that method may doesn’t meet our demand. When we use the new method that proposed in this paper, we can solve the problem. The new method makes an improvement for NEM. By iterative algorithm, the new method uses the gradation data calculated by NEM as initial target value, canceling the relevant aggregate if the result of proportion is negative, and setting the gradation to the boundary value if the target value goes beyond limits. According to the adjusted object value, using NEM again, the new aggregate proportion can be solved. Then the new gradation of mixture will come into being the next target value. Finally, the accurate result will meet our need. The new improved method has good engineering applicability and high accuracy


2019 ◽  
Vol 109 (05) ◽  
pp. 312-318
Author(s):  
T. Engelberth ◽  
A. Verl

Zahnstange-Ritzel-Antriebe werden vorwiegend in großen Werkzeugmaschinen eingesetzt. Um die hohen Genauigkeitsanforderungen moderner Produktionsanlagen zu erreichen, werden diese Antriebe elektrisch verspannt. Die Verspannung ist konstant. Dieser Beitrag beschreibt eine neuartige Methode, die sogenannte adaptive Verspannung. Ziel ist es, den Energiebedarf und die Belastung des Antriebssystems durch Anpassung der Verspannung während des Betriebs zu reduzieren, ohne die Genauigkeit zu beeinflussen.   Rack-and-pinion-drives are mostly used in large machine tools. To achieve the high accuracy specifications of modern production facilities, these drives are electrically preloaded. The preload is constant. This article describes a new method of so-called adaptive preloading. The aim is to reduce energy demand and wear of the drive system by adjusting the preload during operation without affecting the accuracy.


Author(s):  
F. Pineda ◽  
V. Ayma ◽  
C. Beltran

Abstract. High-resolution satellite images have always been in high demand due to the greater detail and precision they offer, as well as the wide scope of the fields in which they could be applied; however, satellites in operation offering very high-resolution (VHR) images has experienced an important increase, but they remain as a smaller proportion against existing lower resolution (HR) satellites. Recent models of convolutional neural networks (CNN) are very suitable for applications with image processing, like resolution enhancement of images; but in order to obtain an acceptable result, it is important, not only to define the kind of CNN architecture but the reference set of images to train the model. Our work proposes an alternative to improve the spatial resolution of HR images obtained by Sentinel-2 satellite by using the VHR images from PeruSat1, a peruvian satellite, which serve as the reference for the super-resolution approach implementation based on a Generative Adversarial Network (GAN) model, as an alternative for obtaining VHR images. The VHR PeruSat-1 image dataset is used for the training process of the network. The results obtained were analyzed considering the Peak Signal to Noise Ratios (PSNR) and the Structural Similarity (SSIM). Finally, some visual outcomes, over a given testing dataset, are presented so the performance of the model could be analyzed as well.


2021 ◽  
Author(s):  
Imen Boujmil ◽  
Giancarlo Ruocco ◽  
Marco Leonetti

Super resolution techniques are an excellent alternative to wide field microscopy, providing high resolution also in (typically fragile) biological sample. Among the various super resolution techniques, Structured Illumination Microscopy (SIM) improve resolution by employing multiple illumination patterns to be deconvolved with a dedicated software. In the case of blind SIM techniques, unknown patterns, such as speckles, are used, thus providing super resolved images, nearly unaffected by aberrations with a simplified experimental setup. Scattering Assisted Imaging, a special blind SIM technique, exploits an illumination PSF (speckle grains size), smaller than the collection PSF (defined by the collection objectives), to surpass the typical SIM resolution enhancement. However, if SAI is used, it is very difficult to extract the resolution enhancement form a priori considerations. In this paper we propose a protocol and experimental setup for the resolution measurement, demonstrating the resolution enhancement for different collection PSF values.


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