scholarly journals Astronomical Image Compression Techniques Based on ACC and KLT Coder

10.14311/1336 ◽  
2011 ◽  
Vol 51 (1) ◽  
Author(s):  
J. Schindler ◽  
P. Páta ◽  
M. Klíma ◽  
K. Fliegel
Keyword(s):  
Gamma Ray ◽  
Image Data ◽  
Point Of View ◽  
Uniform Quantization ◽  
Reduction Methods ◽  
Testing Signal ◽  
Astronomical Images ◽  
Karhunen Loeve Transform ◽  
Robotic Telescope ◽  
Optical Transient

This paper deals with a compression of image data in applications in astronomy. Astronomical images have typical specific properties — high grayscale bit depth, size, noise occurrence and special processing algorithms. They belong to the class of scientific images. Their processing and compression is quite different from the classical approach of multimedia image processing. The database of images from BOOTES (Burst Observer and Optical Transient Exploring System) has been chosen as a source of the testing signal. BOOTES is a Czech-Spanish robotic telescope for observing AGN (active galactic nuclei) and the optical transient of GRB (gamma ray bursts) searching. This paper discusses an approach based on an analysis of statistical properties of image data. A comparison of two irrelevancy reduction methods is presented from a scientific (astrometric and photometric) point of view. The first method is based on a statistical approach, using the Karhunen-Loeve transform (KLT) with uniform quantization in the spectral domain. The second technique is derived from wavelet decomposition with adaptive selection of used prediction coefficients. Finally, the comparison of three redundancy reduction methods is discussed. Multimedia format JPEG2000 and HCOMPRESS, designed especially for astronomical images, are compared with the new Astronomical Context Coder (ACC) coder based on adaptive median regression.

scholarly journals The Zadko Telescope: A Southern Hemisphere Telescope for Optical Transient Searches, Multi-Messenger Astronomy and Education

2010 ◽  
Vol 27 (3) ◽  
pp. 331-339 ◽  
Author(s):  
D. M. Coward ◽  
M. Todd ◽  
T. P. Vaalsta ◽  
M. Laas-Bourez ◽  
A. Klotz ◽  
...  
Keyword(s):  
East Coast ◽  
Gamma Ray ◽  
High Energy ◽  
Pilot Program ◽  
Public Outreach ◽  
Southern Latitude ◽  
Optical Transients ◽  
Robotic Telescope ◽  
Optical Transient ◽  
Potential Tool

AbstractThe new 1 m f/4 fast-slew Zadko Telescope was installed in June 2008 about 70 km north of Perth, Western Australia. It is the only metre-class optical facility at this southern latitude between the east coast of Australia and South Africa, and can rapidly image optical transients at a longitude not monitored by other similar facilities. We report on first imaging tests of a pilot program of minor planet searches, and Target of Opportunity observations triggered by the Swift satellite. In 12 months, 6 gamma-ray burst afterglows were detected, with estimated magnitudes; two of them, GRB 090205 (z = 4.65) and GRB 090516 (z = 4.11), are among the most distant optical transients imaged by an Australian telescope. Many asteroids were observed in a systematic 3-month search. In September 2009, an automatic telescope control system was installed, which will be used to link the facility to a global robotic telescope network; future targets will include fast optical transients triggered by high-energy satellites, radio transient detections, and LIGO gravitational wave candidate events. We also outline the importance of the facility as a potential tool for education, training, and public outreach.

scholarly journals The Impact of KLT Coder on the Image Distortion in Astronomy

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Petr Pata
Keyword(s):  
Image Data ◽  
Image Distortion ◽  
Point Of View ◽  
The Novel ◽  
Gaussian Probability Density Function ◽  
Novel Approach ◽  
Spread Function ◽  
Karhunen Loeve Transform ◽  
Astronomical Image Processing ◽  
The Impact

Presented paper is devoted to the application of Karhunen-Loève transform (KLT) for compression and to study of KLT impact on the image distortion in astronomy. This transform is an optimal fit for images with Gaussian probability density function in order to minimize the root mean square error (RMSE). The main part of the encoder is proposed in relation to statistical image properties. Selected astronomical image processing algorithms are used for the encoder testing. The astrometry and point spread function distortion are selected as the most important criteria. The results are compared with JPEG2000 standard. The KLT encoder provides better results from the RMSE point of view. These results are promising and show the novel approach to the design of lossy image compression algorithms and also suitability for algorithms of image data structuring for retrieving, transfer, and distribution.

scholarly journals Unsupervised Text Feature Learning via Deep Variational Auto-encoder

2020 ◽  
Vol 49 (3) ◽  
pp. 421-437
Author(s):  
Genggeng Liu ◽  
Lin Xie ◽  
Chi-Hua Chen
Keyword(s):  
Dimensionality Reduction ◽  
High Dimensional Data ◽  
Image Data ◽  
Original Data ◽  
Feature Representation ◽  
High Dimensional ◽  
Learning To Learn ◽  
Text Feature ◽  
Reduction Methods ◽  
Low Dimensional

Dimensionality reduction plays an important role in the data processing of machine learning and data mining, which makes the processing of high-dimensional data more efficient. Dimensionality reduction can extract the low-dimensional feature representation of high-dimensional data, and an effective dimensionality reduction method can not only extract most of the useful information of the original data, but also realize the function of removing useless noise. The dimensionality reduction methods can be applied to all types of data, especially image data. Although the supervised learning method has achieved good results in the application of dimensionality reduction, its performance depends on the number of labeled training samples. With the growing of information from internet, marking the data requires more resources and is more difficult. Therefore, using unsupervised learning to learn the feature of data has extremely important research value. In this paper, an unsupervised multilayered variational auto-encoder model is studied in the text data, so that the high-dimensional feature to the low-dimensional feature becomes efficient and the low-dimensional feature can retain mainly information as much as possible. Low-dimensional feature obtained by different dimensionality reduction methods are used to compare with the dimensionality reduction results of variational auto-encoder (VAE), and the method can be significantly improved over other comparison methods.

scholarly journals Improving the Photometry of the Pi of the Sky System

10.14311/1342 ◽  
2011 ◽  
Vol 51 (1) ◽  
Author(s):  
A. F. Żarnecki ◽  
K. Małek ◽  
M. Sokołowski
Keyword(s):  
Gamma Ray ◽  
Field Of View ◽  
Good Time ◽  
Calibration Algorithm ◽  
Sophisticated Instrument ◽  
The Stability ◽  
Robotic Telescope ◽  
Prototype Detector ◽  
Good Time Resolution ◽  
Supernovae Stars

The “Pi of the Sky” robotic telescope was designed to monitor a significant fraction of the sky with good time resolution and range. The main goal of the “Pi of the Sky” detector is to look for short timescale optical transients arising from various astrophysical phenomena, mainly for the optical counterparts of Gamma Ray Bursts (GRB). The system design, the observation methodology and the algorithms that have been developed make this detector a sophisticated instrument for looking for novae and supernovae stars and for monitoring blasars and AGNs activity. The final detector will consist of two sets of 12 cameras, one camera covering a field of view of 20◦ ×20◦. For data taken with the prototype detector at the Las Campanas Observatory, Chile, photometry uncertainty of 0.018–0.024 magnitudo for stars 7–10m was obtained. With a new calibration algorithm taking into account the spectral type of reference stars, the stability of the photometry algorithm can be significantly improved. Preliminary results from the BGInd variable are presented, showing that uncertainty of the order of 0.013 can be obtained.

scholarly journals Semantically Linking Specimens and Images

2019 ◽  
Vol 3 ◽  
Author(s):  
Roger Hyam
Keyword(s):  
High Resolution ◽  
Natural History ◽  
Image Data ◽  
Application Programming Interface ◽  
Point Of View ◽  
Software Systems ◽  
Semantic Data ◽  
Metadata Record ◽  
Natural History Collections ◽  
The Web

Many of the world’s natural history collections are creating high resolution digital images of their specimens. They often make these available on the web through some form or zoomable viewer. For historical reasons, a hotchpotch of technologies are used to achieve this. This diversity has lead to two issues. Firstly, maintenance becomes costly as technologies need replacing. Secondly there is little chance to share data between institutions or provide a unified user experience. A researcher visiting four different virtual collections may have four very different experiences. Similar issues exist in the archives and libraries disciplines. They also need to share high resolution, annotated images of the physical objects in their care. In response to this issue many have coalesced around the International Image Interoperability Framework (IIIF). IIIF is a set of shared application programming interface (API) specifications for interoperable functionality in digital image repositories. It separates the notion of a viewer, which may be used as part of a website or other application, and the web services that feed data to that viewer. By using a common API for serving data about images, different viewers can be used to view the same images, thus providing an upgrade path that does not require replacement of viewer and server software at the same time and allows different viewers to be used for the same image data. Potentially more importantly, it facilitates the construction of applications that view data from different collections as if they were in the same place. From the researcher’s point of view, the experience could be the same whether the virtual specimen is hosted locally or in a museum on another continent. There is one important thing that has been deliberately omitted from the IIIF standard. This has both enabled its rapid adoption but also makes it incomplete for building research applications. IIIF transmits no semantic data about the subject of the images, only labels. The IIIF data therefore needs to be bound to semantically rich data about the specimens being viewed, in some uniform way. Consortium of Taxonomic Facilities (CETAF ) specimen identifiers are now widely adopted by natural history collections in Europe. Each individual collection object is designated by a URI chosen and maintained by the institution owning the specimen (Groom et al. 2017, Güntsch et al. 2018, Güntsch et al. 2017, HYAM et al. 2012). Under Linked Data conventions, content negotiation is used at the server so that users accessing an object using a web-browser are redirected to a human-readable representation of the object, typically a web-page, whilst software systems requiring machine-processable representations are redirected to an RDF-encoded metadata record. CETAF specimen identifiers are therefore ideal partners for IIIF representations of specimens. But how should we join the two together in a semantically rich way that will be generally understandable? SYNTHESYS+ is a European Commission funded programme that facilitates collaboration and network building among European natural history collections. It is concerned with both physical and virtual access to the 390 million specimens of plants and animals housed in participating institutions. Under Task 4.3 of this project, we have been working to create a reliable way to link between the RDF metadata about specimens and images of those specimens in IIIF as well as from images of specimens back to metadata of those specimens. By January 2021, we aim to have ten exemplar institutions publishing IIIF manifest files linked to CETAF identifiers for a few million specimens and for this to act as a catalyst for wider adoption in the natural history community. This presentation gives an update on the rollout of these implementations, paying particular attention to the challenges of semantically annotating specimens with images.

scholarly journals Externally Acquired Radiological Image Data and Reporting for the Clinical Routine, Conference and Boards – Legal Aspects of the Second Opinion in Germany

2018 ◽  
Vol 190 (07) ◽  
pp. 610-615 ◽  
Author(s):  
Andreas Schreyer ◽  
Britta Rosenberg ◽  
René Steinhäuser
Keyword(s):  
Image Data ◽  
Legal Aspects ◽  
Point Of View ◽  
Second Opinion ◽  
Radiological Data ◽  
Key Points ◽  
Written Form ◽  
Radiological Image ◽  
Attending Physician ◽  
Previous Image

Background Because of an increasing number of boards and conferences, the number of second opinion readings of externally acquired image data is growing dramatically. In this review article we intend to give medical and legal recommendations for the documentation and interpretation of externally acquired radiological data for second opinions and board presentations based on German jurisdiction. Method Using the FAQ format as a dialog between radiologists and medical legal experts, we answer the most crucial questions regarding correct documentation and interpretation for externally acquired radiological image data based on an up-to-date literature search. Results Based on the unity of radiological image data and the corresponding written report according to the radiation protection law, the primary report should be present when composing a second opinion. If the primary external report is not present, this should be mentioned as a limitation. All radiological second opinions should be documented in written form. This is especially important in cases of discrepant findings. Legally, the attending physician is responsible for selecting the radiological opinion. The radiologist should not rely on the written primary report without personal reevaluation. Legally, it would be considered radiological malpractice if the external image data and previous image data are not evaluated personally. Conclusion From a legal point of view, there are explicit recommendations regarding thorough documentation of a second opinion as an independent medical service in all cases. Key Points  Citation Format

scholarly journals CNN-Based Deep Architecture for Health Monitoring of Civil and Industrial Structures Using UAVs

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 69
Author(s):  
Thomas Harweg ◽  
Annika Peters ◽  
Daniel Bachmann ◽  
Frank Weichert
Keyword(s):  
Health Monitoring ◽  
Real Life ◽  
Image Data ◽  
Steel Structures ◽  
Point Of View ◽  
Object Localization ◽  
Data Annotation ◽  
Industrial Structures ◽  
Multi Stage ◽  
Novel Approach

Health monitoring of civil and industrial structures has been gaining importance since the collapse of the bridge in Genoa (Italy). It is vital for the creation and maintenance of reliable infrastructure. Traditional manual inspections for this task are crucial but time consuming. We present a novel approach for combining Unmanned Aerial Vehicles (UAVs) and artificial intelligence to tackle the above-mentioned challenges. Modern architectures in Convolutional Neural Networks (CNNs) were adapted to the special characteristics of data streams gathered from UAV visual sensors. The approach allows for automated detection and localization of various damages to steel structures, coatings, and fasteners, e.g., cracks or corrosion, under uncertain and real-life environments. The proposed model is based on a multi-stage cascaded classifier to account for the variety of detail level from the optical sensor captured during an UAV flight. This allows for reconciliation of the characteristics of gathered image data and crucial aspects from a steel engineer’s point of view. To improve performance of the system and minimize manual data annotation, we use transfer learning based on the well-known COCO dataset combined with field inspection images. This approach provides a solid data basis for object localization and classification with state-of-the-art CNN architectures.

Reduction Methods of Structure Models for Control System Purposes

2016 ◽  
Vol 248 ◽  
pp. 119-126 ◽  
Author(s):  
Andrzej Koszewnik ◽  
Zdzisław Gosiewski
Keyword(s):  
Control System ◽  
High Frequency ◽  
Closed Loop ◽  
Flexible Structures ◽  
Low Frequency ◽  
Point Of View ◽  
Closed Loop Systems ◽  
System A ◽  
Reduction Methods ◽  
The Stability

To design vibration control system for flexible structures their mathematical model should be reduced. In the paper we consider the influence of the model reduction on the dynamics of the real closed-loop system. A simply cantilever beam is an object of consideration since we are able to formulate the exact analytical model of such structure. As a result of reduction the model with low frequency resonances is usually separated from the high frequency dynamics because high frequency part of the model is naturally strong damped. In order to estimate dynamical system for control purposes in the paper we applied a few orthogonal methods such as: modal, Rayleigh-Ritz and Schur decompositions. As it is shown all methods well calculate resonances frequencies but generate different anti-resonances frequencies. From control strategy in point of view of the flexible structures these anti-resonances have significantly influence on the stability and dynamics of the closed-loop systems.

scholarly journals FRAM—The Robotic Telescope for the Monitoring of the Wavelength Dependence of the Extinction: Description of Hardware, Data Analysis, and Results

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Michael Prouza ◽  
Martin Jelínek ◽  
Petr Kubánek ◽  
Jan Ebr ◽  
Petr Trávníček ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Ccd Camera ◽  
Cosmic Ray ◽  
Wavelength Dependence ◽  
Light Extinction ◽  
Wide Field ◽  
Atmospheric Conditions ◽  
Optical Telescope ◽  
Rapid Monitoring ◽  
Robotic Telescope

FRAM—F/(Ph)otometric Robotic Atmospheric Monitor is one of the atmospheric monitoring instruments at the Pierre Auger Observatory in Argentina. FRAM is an optical telescope equipped with CCD cameras and photometer, and it automatically observes a set of selected standard stars. Primarily, FRAM observations are used to obtain the wavelength dependence of the light extinction. FRAM telescope is also able to observe secondary astronomical targets, and namely the detection of optical counterparts of gamma-ray bursts has already proven to be successful. Finally, a wide-field CCD camera of FRAM can be used for rapid monitoring of atmospheric conditions along the track of particularly interesting cosmic ray showers. The hardware setup of the telescope, its software system, data taking procedures, and results of analysis are described in this paper.

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