scholarly journals Vis3D+ A tightly integrated GPU-accelerated computation and rendering framework for interactive 3D image visualization

2021 ◽  
Author(s):  
Irfa Nisar
Keyword(s):  
Image Processing ◽  
Graphics Processing Units ◽  
General Purpose ◽  
Graphics Hardware ◽  
3D Image ◽  
Image Processing Algorithm ◽  
Image Visualization ◽  
Computing Platform ◽  
Software Modules ◽  
Interactive 3D

This thesis presents extensions to an interactive 3D image visualization framework. The existing software framework provides functionality for interactively visualizing 3D medical data. The extensions consist of software modules that execute directly on the graphics hardware, utilizing the massively parallel, general-purpose computing platform provided by modern graphics processing units (GPUs). These GPUbased software modules are designed to support the execution of volume image processing algorithms, implemented using recently available GPU programs known as “compute shaders”, as well as to support interactive editing of the algorithms’ output. The new modules are seamlessly integrated as new stages in a GPU-based rendering pipeline provided by the existing framework. In this thesis, an example volume image processing algorithm known as level set segmentation is implemented and demonstrated. In addition, a new editing module is demonstrated that enables user modification of this algorithm’s output by extending a pre-existing volume “painting” interface.

scholarly journals Vis3D+ A tightly integrated GPU-accelerated computation and rendering framework for interactive 3D image visualization

2021 ◽  
Author(s):  
Irfa Nisar
Keyword(s):  
Image Processing ◽  
Graphics Processing Units ◽  
General Purpose ◽  
Graphics Hardware ◽  
3D Image ◽  
Image Processing Algorithm ◽  
Image Visualization ◽  
Computing Platform ◽  
Software Modules ◽  
Interactive 3D

This thesis presents extensions to an interactive 3D image visualization framework. The existing software framework provides functionality for interactively visualizing 3D medical data. The extensions consist of software modules that execute directly on the graphics hardware, utilizing the massively parallel, general-purpose computing platform provided by modern graphics processing units (GPUs). These GPUbased software modules are designed to support the execution of volume image processing algorithms, implemented using recently available GPU programs known as “compute shaders”, as well as to support interactive editing of the algorithms’ output. The new modules are seamlessly integrated as new stages in a GPU-based rendering pipeline provided by the existing framework. In this thesis, an example volume image processing algorithm known as level set segmentation is implemented and demonstrated. In addition, a new editing module is demonstrated that enables user modification of this algorithm’s output by extending a pre-existing volume “painting” interface.

Publishing in International Journal of Automation Technology

2007 ◽  
Vol 1 (1) ◽  
pp. 4-4
Author(s):  
Yusuf Altintas
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Position Control ◽  
Mechanical Design ◽  
Image Processing Algorithm ◽  
Academic Knowledge ◽  
Software Modules ◽  
Integration Of Disciplines ◽  
The Individual ◽  
Automation Technology

Automation technology is created by integrating mechanical design, dynamics, control, sensors, actuators, electronics and real time software engineering knowledge into a single system. While there are a number of journals which focus on the individual subjects, a sole journal like IJAT which presents the integration of disciplines to create automation products has been missing. Although automation covers rather a large spectrum, we encourage the authors to submit their articles with the details of technology integration. While mathematical details of a position control of a single axis machine may be more suitable to be presented in a pure control journal, the integration of mechanical drives, motors, sensors, control law, trajectory generation and real time software modules constitutes an excellent example for an automation technology. Similarly, while an image processing algorithm would be narrow, integration of image processing, timing, coordination with moving machinery, hardware and software lay out describes an automation technology. The aim of the journal is to bring theory, design and integration together which leads to the creation of a novel automation technology. The journal is expected to be a key resource for automation engineers in industry and academia while disseminating archival academic knowledge to the society.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

scholarly journals DSPSR: Digital Signal Processing Software for Pulsar Astronomy

2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Digital Signal ◽  
General Purpose ◽  
Design Decisions ◽  
Extensive Range ◽  
Processing Software ◽  
Graphics Processing

Abstractdspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

Internal quality evaluation of chestnut using nuclear magnetic resonance

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim
Keyword(s):  
Image Processing ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Processing Algorithm ◽  
Internal Quality ◽  
Soluble Solid Content ◽  
Mr Images ◽  
Image Processing Algorithm ◽  
Internal Defects ◽  
Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

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