The Experts below are selected from a list of 83703 Experts worldwide ranked by ideXlab platform
Andreas Engel - One of the best experts on this subject based on the ideXlab platform.
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collaborative em image Processing with the iplt image Processing Library and toolbox
Journal of Structural Biology, 2007Co-Authors: Ansgar Philippsen, Andreas D Schenk, Giani A Signorell, Valerio Mariani, Simon Berneche, Andreas EngelAbstract:We present the Image Processing Library and Toolbox, IPLT, in the context of a collaborative electron microscopy Processing effort, which has driven the evolution of our software architecture over the last years. The high-level interface design as well as the underlying implementations are described to demonstrate the flexibility of the IPLT framework. It aims to support the wide range of skills and interests of methodologically oriented scientists who wish to implement their ideas and algorithms as Processing code.
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iplt image Processing Library and toolkit for the electron microscopy community
Journal of Structural Biology, 2003Co-Authors: Ansgar Philippsen, Andreas D Schenk, Henning Stahlberg, Andreas EngelAbstract:We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image Processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image Processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.
Ansgar Philippsen - One of the best experts on this subject based on the ideXlab platform.
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collaborative em image Processing with the iplt image Processing Library and toolbox
Journal of Structural Biology, 2007Co-Authors: Ansgar Philippsen, Andreas D Schenk, Giani A Signorell, Valerio Mariani, Simon Berneche, Andreas EngelAbstract:We present the Image Processing Library and Toolbox, IPLT, in the context of a collaborative electron microscopy Processing effort, which has driven the evolution of our software architecture over the last years. The high-level interface design as well as the underlying implementations are described to demonstrate the flexibility of the IPLT framework. It aims to support the wide range of skills and interests of methodologically oriented scientists who wish to implement their ideas and algorithms as Processing code.
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iplt image Processing Library and toolkit for the electron microscopy community
Journal of Structural Biology, 2003Co-Authors: Ansgar Philippsen, Andreas D Schenk, Henning Stahlberg, Andreas EngelAbstract:We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image Processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image Processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.
Hiroshi Matsuo - One of the best experts on this subject based on the ideXlab platform.
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content aware precision control on a real time video Processing Library
International Conference on High Performance Computing and Simulation, 2013Co-Authors: Takuya Matsunaga, Tomoaki Tsumura, Shinji Ohira, Hiroshi MatsuoAbstract:The performance of general purpose computers is increasing rapidly, and now they are capable of running video Processing applications. However, on general purpose operating systems, real-time video Processing is still difficult because there is no guarantee that enough CPU resources can surely be provided. A pseudo real-time video Processing Library RaVioli has been proposed for addressing this issue. RaVioli conceals two resolutions, frame rate and number of pixels, from programmers and provides a dynamic and transparent resolution adjustability. Using RaVioli, pseudo real-time video Processing can be achieved easily, but output precision may be roughened for reducing Processing load. To solve this problem, this paper proposes a new load adjustment method for RaVioli, which can divide whole video frame into several sub-frames, and can process each subframe with appropriate resolution or precision automatically.
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tiling with different spatial resolutions for pseudo real time video Processing Library ravioli
Signal-Image Technology and Internet-Based Systems, 2011Co-Authors: Katsuhiko Kondo, Tomoaki Tsumura, Takafumi Inaba, Ami Ono, Hiroshi MatsuoAbstract:The performance of general purpose computers is increasing rapidly, and now they are capable of running video Processing applications. However, on general purpose operating systems, real-time video Processing is still difficult because there is no guarantee that enough CPU resources can surely be provided. A pseudo real-time video Processing Library RaVioli has been proposed for solving this issue. RaVioli conceals two resolutions, frame rate and number of pixels, from programmers and provides a dynamic and transparent resolution adjustability. Using RaVioli, pseudo real-time video Processing can be achieved easily, but output precision may be roughened for reducing Processing load. To prevent this situation, this paper proposes a method for automatically dividing whole video frame into several sub frames, or tiles, and changing the resolutions of each tile individually. We have implemented the method on RaVioli and have made some evaluations with a sample program. The result shows that the proposed method can keep the resolution of video frames higher than traditional RaVioli.
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ravioli a gpu supported high level pseudo real time video Processing Library
Proc. 19th Int'l Conf. on Computer Graphics Visualization and Computer Vision (WSCG' 2011), 2011Co-Authors: Katsuhiko Kondo, Hiroko Sakurai, Masaomi Ohno, Tomoaki Tsumura, Takafumi Inaba, Hiroshi MatsuoAbstract:Real-time video Processing applications such as intruder detection system are now in demand and being developed. However, on general purpose computers, it is difficult to guarantee that enough CPU resources can be surely be provided. We have proposed a pseudo real-time video Processing Library RaVioli for solving this problem. RaVioli conceals two types of resolutions, frame rate and the number of pixels, from programmers. This makes video and image Processing programmings more intuitive, but the performance may be lower by the abstraction overhead. To solve this problem, this paper proposes an improvement of RaVioli for supporting GPU platforms. For using GPUs effectively, a deep knowledge about them has been required, and this would have been a burden to programmers. The proposition on this paper provides an easy-to-use framework for developers. They can benefit from GPU without rewriting their RaVioli programs and get high performance video Processing. The experiment results with image/video Processing programs show that the proposed method improves the performance about 151-fold/164-fold in maximum against traditional RaVioli without rewriting programs, and about 30-fold/4-fold in maximum against a native C++ program.
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ravioli a parallel video Processing Library with auto resolution adjustability
IADIS AC (1), 2009Co-Authors: Hiroko Sakurai, Masaomi Ohno, Shintaro Okada, Tomoaki Tsumura, Hiroshi MatsuoAbstract:Video Processing applications are now in demand on a great variety of platforms such as mobile devices or high performance servers. On the other hand, a great variety of performance is required for video Processing applications such as high throughput, good accuracy, long battery life, and so on. Therefore, programmers today should study hard about various platforms and techniques under the pressure of necessity. This must make the burden heavy for them. This paper proposes a parallel video Processing Library RaVioli. RaVioli achieves self-optimizations for multi-core processors and self-adjustment of resolutions. RaVioli conceals two resolutions, frame rate and number of pixels, from users and provides dynamic and transparent resolution adjustability based on user-preferred priority parameters. This makes pseudo real-time video Processing feasible for any platform by adjusting resolutions according to situations. Generally, video Processing has some parallelism in its algorithm. For example, pixels in a frame have data parallelism, and many video Processing algorithms can be divided into some Processing stages which can be pipelined. Concealing resolutions makes implicit parallelism more obvious. Hence, RaVioli can parallelize programs semi-automatically.
Andreas D Schenk - One of the best experts on this subject based on the ideXlab platform.
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collaborative em image Processing with the iplt image Processing Library and toolbox
Journal of Structural Biology, 2007Co-Authors: Ansgar Philippsen, Andreas D Schenk, Giani A Signorell, Valerio Mariani, Simon Berneche, Andreas EngelAbstract:We present the Image Processing Library and Toolbox, IPLT, in the context of a collaborative electron microscopy Processing effort, which has driven the evolution of our software architecture over the last years. The high-level interface design as well as the underlying implementations are described to demonstrate the flexibility of the IPLT framework. It aims to support the wide range of skills and interests of methodologically oriented scientists who wish to implement their ideas and algorithms as Processing code.
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iplt image Processing Library and toolkit for the electron microscopy community
Journal of Structural Biology, 2003Co-Authors: Ansgar Philippsen, Andreas D Schenk, Henning Stahlberg, Andreas EngelAbstract:We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image Processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image Processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.
Jd Shutler - One of the best experts on this subject based on the ideXlab platform.
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Data Processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment
'Elsevier BV', 2016Co-Authors: Bh Taylor, Mg Grant, Jd ShutlerAbstract:This is the author's preprint. The final version is available from the publisher via the DOI in this record.The authors would like to thank Dr. Peter Land for useful discussions on reflectance spectra of ground targets. Fig. 9 contains Ordnance Survey OpenData © Crown copyright and database right 2013. The hyperspectral data used in this report were collected by the Natural Environment Research Council Airborne Research and Survey Facility.Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient Processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for Processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated Processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points. © 2013 Elsevier Ltd
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Data Processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment
'Elsevier BV', 2014Co-Authors: Bh Taylor, Mg Grant, Jd ShutlerAbstract:Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient Processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for Processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated Processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points
