Study on Optical Dot Gain Model Based on Point Spread and Probability Methods

2012 ◽  
Vol 271-272 ◽  
pp. 1434-1440
Author(s):  
Jun Fei Xu ◽  
Jin Lin Xu ◽  
Yong Chi Xu

Optical dot gain is the key point of halftone reconstruction study, and has always been a meaningful topic of theoretical study. The Yule–Nielsen formula is by far the most widely used research method of optical dot gain. However, solving the Yule–Nielsen parameter n remains a difficult problem. This paper disregards solving for the Yule–Nielsen parameter n, analyzes the light scattering and osmotic effect of halftone presswork, deduces the exact expressions of blank area of presswork, and determines the reflectivity of the dot part and halftone presswork according to the point spread function and probability method. Furthermore, this paper analyzes how the optical dot gain depends on the dot area coverage of presswork, ink layer transmittivity, and paper-based spectral reflectivity. In addition, a new algorithm model for optical dot gain is established. By employing the Clapper–Yule Model to calculate the spectral transmittance of printing ink and comparing it with the practical measured spectral reflectivity of the halftone presswork proof, the accuracy of the model established in this paper is fully verified.

2020 ◽  
Vol 2020 (14) ◽  
pp. 306-1-306-6
Author(s):  
Florian Schiffers ◽  
Lionel Fiske ◽  
Pablo Ruiz ◽  
Aggelos K. Katsaggelos ◽  
Oliver Cossairt

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (STPSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.


2013 ◽  
Vol 26 (11) ◽  
pp. 944-952 ◽  
Author(s):  
Huibin Wang ◽  
Rong Zhang ◽  
Zhe Chen ◽  
Lizhong Xu ◽  
Jie Shen

2020 ◽  
Vol 128 (7) ◽  
pp. 1036-1040 ◽  
Author(s):  
N. G. Stsepuro ◽  
G. K. Krasin ◽  
M. S. Kovalev ◽  
V. N. Pestereva

2014 ◽  
Author(s):  
Jingyu Yang ◽  
Bin Jiang ◽  
Jinlong Ma ◽  
Yi Sun ◽  
Ming Di

2005 ◽  
Vol 52 (12) ◽  
pp. 1695-1728 ◽  
Author(s):  
C. Van der Avoort * ◽  
J. J. M. Braat ◽  
P. Dirksen ◽  
A. J. E. M. Janssen

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