image geolocalization has become an important research field during the last decade. This field is divided into two main sections. The first is image geolocalization that is used to find out which country, region or c...
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image geolocalization has become an important research field during the last decade. This field is divided into two main sections. The first is image geolocalization that is used to find out which country, region or city the image belongs to. The second one is refining image localization for uses that require more accuracy such as augmented reality and three dimensional environment reconstruction using images. In this paper we present a processing chain that gathers geographic datafrom several sources in order to deliver a better geolocalization than the GPS one of an image and precise camera pose parameters. In order to do so, we use multiple types of data. Among this information some are visible in the image and are extracted using image processing, other types of data can be extracted fromimage file headers or online image sharing platforms related information. Extracted information elements will not be expressive enough if they remain disconnected. We show that grouping these information elements helps finding the best geolocalization of the image.
The Internet of Things (IoT) has attracted significant attention from both academia and industry, thanks to applications such as smart cities, smart buildings and intelligent traffic management. These systems rely on ...
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ISBN:
(纸本)9781538664889
The Internet of Things (IoT) has attracted significant attention from both academia and industry, thanks to applications such as smart cities, smart buildings and intelligent traffic management. These systems rely on data, collected from IoT devices, that are sent to the cloud for analytics. data are either used for near real-time decisions or stored for long-term analysis. However, in highly distributed IoT systems, missing or invalid data may appear because of different reasons including sensor failures, monitoring system failures and network failures. Analyzing incompletedatasets can lead to inaccurate results and imprecise decisions, with negative effects on the target systems. Also, due to the increasing size of such systems and the consequently increasing amount of data generated from sensors, recovery of incompletedatasets for analytics on the cloud is often infeasible, due to the limited bandwidth available and the strict latency constraints of IoT applications. We propose a novel semi-automatic recursive mechanism for recovery of incompletedatasets on the edge that is closer to the source of data. This mechanism enables efficient recovery of incompletedatasets employing different forecasting techniques for multiple gaps, based on user specifications. We evaluate our approach on datasets coming from the context of smart buildings and smart homes. The experimental results show that our approach is able to identify multiple gaps, then recover incompletedatasets, decreasing forecasting error by up to 82.68%, and reducing running time by up to 52.38%.
In this paper, we describe a practical implementation of an imagereconstruction method designed to generate a map of the brightness distribution fromdata consisting of squared visibilities and complex closure amplit...
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ISBN:
(纸本)9780819482969
In this paper, we describe a practical implementation of an imagereconstruction method designed to generate a map of the brightness distribution fromdata consisting of squared visibilities and complex closure amplitudes resulting from observations of an astronomical target with a broadband, multichannel, spatial optical interferometer. Given the data, the method estimates the true brightness distribution with a model sampled on a rectangular grid of discrete positions on the sky with the assumption that the model intensities in the region not defined by the discrete positions being described by bilinear interpolation of the discrete intensities. The developed imagereconstruction method has been applied to real observational data obtained from existing optical interferometer facilities.
In various situations there is a need to measure and transmit fast moving data such as in Radar, Oceanography, Continuous Monitoring of Meteorological Parameters, etc. It may sometimes happen that some data gets lost....
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ISBN:
(纸本)9781509023998
In various situations there is a need to measure and transmit fast moving data such as in Radar, Oceanography, Continuous Monitoring of Meteorological Parameters, etc. It may sometimes happen that some data gets lost. So to recover this information complete original data is to be resent. In this paper, we have discussed a new type of signal acquisition theory called as Compressive Sensing (CS). Signals having Sparse representation in one or the other domain can be faithfully reconstructed from the random undersampled measurements. Naturally occurring signals such as audio signals are having sparse nature in Fourier Domain. One such implementation of CS theory is also explained and demonstrated. Greedy Algorithm known as Orthogonal Matching Pursuit is used in recovery process.
This paper presents a method for 3D imagereconstruction, which is one of the most attractive avenues in digital image processing techniques, especially due to its application in biomedical imaging. The diversity and ...
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In this research study, an investigation of the benefit of wavelet-based image fusion algorithm for enhancing the quality of the reconstructed images in a multi-frequency microwave tomography was conducted. The microw...
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ISBN:
(纸本)9781728130163
In this research study, an investigation of the benefit of wavelet-based image fusion algorithm for enhancing the quality of the reconstructed images in a multi-frequency microwave tomography was conducted. The microwave tomography system which consists of a PocketVNA, a pair of Vivaldi antenna and a set of Arduino-based electromechanical system was used to acquire the scattering wave around an object being observed. The electromechanical was used to move the angular positions of the Vivaldi antenna pair in the scanning process in order to measure the reflection coefficient (S11), magnitude and phase of the microwaves interacted with observed object material. The Vivaldi antenna works in the range of 1.5 - 9.0 GHz, while the PocketVNA operates in range of 500 kHz - 4 GHz. Experiments were done to test the performance of the system with types of materials of different shapes and sizes. The reflection coefficient data (S11) resolved and reconstructed into an image via MATLAB based on Born approximation reconstruction algorithm. imagereconstruction per single frequency is done sequentially from low frequency to high frequency, with a total of 6 different frequency values. A multi-frequency approach will be done by combining the element of stability from the effect of using low frequencies and high-resolution element from the effect of relatively higher frequency usage. The use of multi-frequency reduces nonlinearity problem and increases the stability to get an optimal imagereconstruction. The used image fusion algorithm was also tested using the datasets from Fresnel Institute in order to verify its performance. The image yielded from the image fusion algorithm has a significant increasing image quality compared to the individual images from the reconstruction process resulted on single frequency usage without the image fusion process.
Discrete tomography generally focus on binary imagereconstructionfrom two projections. The Mojette transform allows for a more general framework with any kind of values and any number of projections. Here we use the...
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In September 2018, photogrammetric images and terrestrial laser scans were carried out as part of a measurement campaign for the three-dimensional recording of several historic churches in Tbilisi (Georgia). The aim w...
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In September 2018, photogrammetric images and terrestrial laser scans were carried out as part of a measurement campaign for the three-dimensional recording of several historic churches in Tbilisi (Georgia). The aim was the complete spatial reconstruction with a spatial resolution and accuracy of approx. 1 cm under partly difficult external conditions, which required the use of different measurement techniques. The local measurement data were collected by two laser scanning campaigns (Leica BLK360 and Faro Focus 3D X330), two UAV flights and two terrestrial image sets. The photogrammetric point clouds were calculated with the SfM programs AgiSoft PhotoScan and RealityCapture taking into account the control points from the Faro laser scan. The mean residual errors from the registrations or photogrammetric evaluations are 4-12mm, depending on the selected software. The best completeness and quality of the resulting 3D model was achieved by using laserscan data andimages simultaneously.
Compressed Sensing (CS) or Compressive Sampling offers an improved data acquisition rate for Parallel Magnetic Resonance Imaging (pMRI) systems to achieve reduced scanning time. In pMRI, the optimization of image qual...
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ISBN:
(纸本)9781509044429
Compressed Sensing (CS) or Compressive Sampling offers an improved data acquisition rate for Parallel Magnetic Resonance Imaging (pMRI) systems to achieve reduced scanning time. In pMRI, the optimization of image quality is done through appropriate selection/ placement of coils according to the anatomy of the object to be imaged. This paper proposes an efficient interferometric modulation scheme for radio frequency (RF) receiver coils of parallel MRI (pMRI) that produces magnetization field over the object. The modulated magnetization field is beneficial for improving estimation accuracy of sensitivity profiles which enhance reconstruction quality at high data acquisition rate. A CS regularized sensitivity encoding approach is used as reconstruction technique in which the required MR image is provided through an iterative optimization process from the under-sampled observed k-space data. Extensive simulation results show a significant reduction in artifacts and thereby consequent visual improvement in the reconstructed MR images are achieved even when a high rate of acceleration factor is used. Simulation results also demonstrate that the proposed method outperforms some state-of-the-art pMRI methods, both in terms of subjective and objective quality assessment for the reconstructed images.
The proceedings contain 11 papers. The special focus in this conference is on Simulation and Synthesis in Medical Imaging. The topics include: Adversarial image synthesis for unpaired multi-modal cardiac data;deep MR ...
ISBN:
(纸本)9783319681269
The proceedings contain 11 papers. The special focus in this conference is on Simulation and Synthesis in Medical Imaging. The topics include: Adversarial image synthesis for unpaired multi-modal cardiac data;deep MR to CT synthesis using unpaired data;synthesizing CT from ultrashort echo-time MR images via convolutional neural networks;a supervoxel based random forest synthesis framework for bidirectional MR/CT synthesis;region-enhanced joint dictionary learning for cross-modality synthesis in diffusion tensor imaging;virtual PET images from CT data using deep convolutional networks;semi-supervised assessment of incomplete LV coverage in cardiac MRI using generative adversarial nets;high order slice interpolation for medical images;a monte carlo framework for low dose CT reconstruction testing;multimodal simulations in live cell imaging;medical image processing and numerical simulation for digital hepatic parenchymal blood flow.
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