scholarly journals Extraction of three-dimensional fracture trace maps from calibrated image sequences

Geosphere ◽  
2016 ◽  
Vol 12 (4) ◽  
pp. 1323-1340 ◽  
Author(s):  
Thomas D. Seers ◽  
David Hodgetts
Keyword(s):  
Three Dimensional ◽  
Image Sequences ◽  
Trace Maps

A Video Super Resolution Algorithm Based on Wavelet Coefficient

2014 ◽  
Vol 610 ◽  
pp. 425-428
Author(s):  
Wei Jian Liu ◽  
Si Da Xiao ◽  
Ruo He Yao
Keyword(s):  
High Frequency ◽  
Wavelet Coefficient ◽  
Three Dimensional ◽  
Super Resolution ◽  
Structural Similarity ◽  
Image Sequences ◽  
Discrete Wavelet ◽  
Resolution Image ◽  
Resolution Algorithm ◽  
Visual Results

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

scholarly journals On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Jeyarajan Thiyagalingam ◽  
Daniel Goodman ◽  
Julia A. Schnabel ◽  
Anne Trefethen ◽  
Vicente Grau
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Three Dimensional ◽  
Basic Research ◽  
Estimation Algorithm ◽  
Image Sequences ◽  
Multicore Architectures ◽  
Gpu Architectures ◽  
Access Patterns ◽  
Performance Gains

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results.

scholarly journals The Use of Gigapixel Photogrammetry for the Understanding of Landslide Processes in Alpine Terrain

Geosciences ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 99 ◽  
Author(s):  
Saverio Romeo ◽  
Lucio Di Matteo ◽  
Daniel Kieffer ◽  
Grazia Tosi ◽  
Aurelio Stoppini ◽  
...  
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Image Sequences ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Experimental Application ◽  
Single Lens ◽  
Landslide Processes ◽  
3D Information

The work in this paper illustrates an experimental application for geosciences by coupling new and low cost photogrammetric techniques: Gigapixel and Structure-from-Motion (SfM). Gigapixel photography is a digital image composed of billions of pixels (≥1000 megapixels) obtained from a conventional Digital single-lens reflex camera (DSLR), whereas the SfM technique obtains three-dimensional (3D) information from two-dimensional (2D) image sequences. The field test was carried out at the Ingelsberg slope (Bad Hofgastein, Austria), which hosts one of the most dangerous landslides in the Salzburg Land. The stereographic analysis carried out on the preliminary 3D model, integrated with Ground Based Synthetic Aperture Radar Interferometry (GBInSAR) data, allowed us to obtain the main fractures and discontinuities of the unstable rock mass.

scholarly journals 3D Measurement of Human Chest and Abdomen Surface Based on 3D Fourier Transform and Time Phase Unwrapping

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1091 ◽  
Author(s):  
Haibin Wu ◽  
Shuang Yu ◽  
Xiaoyang Yu
Keyword(s):  
Fourier Transform ◽  
Phase Error ◽  
Three Dimensional ◽  
Image Sequences ◽  
Current Approach ◽  
Individual Characteristics ◽  
Phase Unwrapping ◽  
3D Measurement ◽  
Human Experiments ◽  
The Difference

Monitoring respiratory movements is an effective way to improve radiotherapy treatments of thoracic and abdominal tumors, but the current approach is limited to measuring specific points in the chest and abdomen. In this paper, a dynamic three-dimensional (3D) measurement approach of the human chest and abdomen surface is proposed, which can infer tumor movement more accurately, so the radiotherapy damage to the human body can be reduced. Firstly, color stripe patterns in the RGB color model are projected, then after color correction, the collected stripe image sequences are separated into the three RGB primary color stripe image sequences. Secondly, a fringe projection approach is used to extract the folded phase combined 3D Fourier transform with 3D Gaussian filtering. By the relationship between adjacent fringe images in the time sequence, Gaussian filter parameters with individual characteristics are designed and optimized to improve the accuracy of wrapped phase extraction. In addition, based on the difference between the fractional parts of the folded phase error, one remainder equation can be determined, which is used for time-phase unwrapping. The simulation model and human experiments show that the proposed approach can obtain the 3D image sequences of the chest and abdomen surface in respiratory motion effectively and accurately with strong anti-interference ability.

RECOVERY OF NONRIGID STRUCTURES FROM 2D OBSERVATIONS

2008 ◽  
Vol 22 (02) ◽  
pp. 279-294 ◽  
Author(s):  
HUIYU ZHOU ◽  
XUELONG LI ◽  
TANGWEI LIU ◽  
FAQUAN LIN ◽  
YUSHENG PANG ◽  
...  
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
Image Sequences ◽  
Nonrigid Motion ◽  
Feature Points ◽  
Variance Estimator ◽  
Deformable Structure ◽  
Non Gaussian ◽  
2D Data ◽  
Rigid Component

We present a new method for simultaneously determining three-dimensional (3D) motion and structure of a nonrigid object from its uncalibrated two-dimensional (2D) data with Gaussian or non-Gaussian distributions. A nonrigid motion can be treated as a combination of a rigid component and a nonrigid deformation. To reduce the high dimensionality of the deformable structure or shape, we estimate the probability distribution function (PDF) of the structure through random sampling, integrating an established probabilistic model. The fitting between the observations and the estimated 3D structure will be evaluated using the pooled variance estimator. The recovered structure is only available when the 2D feature points have been properly corresponded over two image frames. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.

Velocity estimation of spots in three-dimensional confocal image sequences of living cells

Cytometry ◽  
2001 ◽  
Vol 43 (4) ◽  
pp. 261-272 ◽  
Author(s):  
C.B.J. Bergsma ◽  
G.J. Streekstra ◽  
A.W.M. Smeulders ◽  
E.M.M. Manders
Keyword(s):  
Three Dimensional ◽  
Living Cells ◽  
Image Sequences ◽  
Velocity Estimation ◽  
Confocal Image
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