scholarly journals Physically based computer graphics for realistic image formation to simulate optical measurement systems

2017 ◽  
Vol 6 (1) ◽  
pp. 171-184 ◽  
Author(s):  
Max-Gerd Retzlaff ◽  
Johannes Hanika ◽  
Jürgen Beyerer ◽  
Carsten Dachsbacher

Abstract. Physically based image synthesis methods, a research direction in computer graphics (CG), are capable of simulating optical measuring systems in their entirety and thus constitute an interesting approach for the development, simulation, optimization, and validation of such systems. In addition, other CG methods, so-called procedural modeling techniques, can be used to quickly generate large sets of virtual samples and scenes thereof that comprise the same variety as physical testing objects and real scenes (e.g., if digitized sample data are not available or difficult to acquire). Appropriate image synthesis (rendering) techniques result in a realistic image formation for the virtual scenes, considering light sources, material, complex lens systems, and sensor properties, and can be used to evaluate and improve complex measuring systems and automated optical inspection (AOI) systems independent of a physical realization. In this paper, we provide an overview of suitable image synthesis methods and their characteristics, we discuss the challenges for the design and specification of a given measuring situation in order to allow for a reliable simulation and validation, and we describe an image generation pipeline suitable for the evaluation and optimization of measuring and AOI systems.

2014 ◽  
Vol 998-999 ◽  
pp. 806-813
Author(s):  
Jian Wang ◽  
Qing Xu

Realistic image synthesis technology is an important part in computer graphics. Monte Carlo based light simulation methods, such as Monte Carlo path tracing, can deal with complex lighting computations for complex scenes, in the field of realistic image synthesis. Unfortunately, if the samples taken for each pixel are not enough, the generated images have a lot of random noise. Adaptive sampling is attractive to reduce image noise. This paper proposes a new GH-distance based adaptive sampling algorithm. Experimental results show that the method can perform better than other similar ones.


2009 ◽  
Author(s):  
Changbo Wang ◽  
Zhuopeng Zhang ◽  
Hongyan Quan ◽  
Zhangye Wang ◽  
Lin Wei

2012 ◽  
Vol 31 (2pt3) ◽  
pp. 545-554 ◽  
Author(s):  
Robert Herzog ◽  
Martin Čadík ◽  
Tunç O. Aydčin ◽  
Kwang In Kim ◽  
Karol Myszkowski ◽  
...  

1986 ◽  
Vol 6 (3) ◽  
pp. 26-35 ◽  
Author(s):  
Michael Cohen ◽  
Donald Greenberg ◽  
David Immel ◽  
Philip Brock

Author(s):  
Andrey Zhdanov ◽  
Dmitry Zhdanov ◽  
Vladimir Galaktionov

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