Dr. Ching Seong Tan Profile

Dr. Ching Seong Tan

Associate Professor at TerraPhoenix

SPIE Involvement:

Author

Publications (9)

Proceedings Article | 10 February 2017 Paper

Performance of range gated reconstruction: a theoretical analysis

Sing Yee Chua, Xin Wang, Ningqun Guo, Ching Seong Tan

Proceedings Volume 10250, 102501P (2017) https://doi.org/10.1117/12.2266638

KEYWORDS: Ranging

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Proceedings Article | 7 January 2015 Paper

Multi-layer surface profiling using gated wavefront sensing

Xin Wang, Nur Dalilla Nordin, Eddy Chow Mun Tik, ChingSeong Tan, Kuew Wai Chew, Carmen Menoni

Proceedings Volume 9442, 94421K (2015) https://doi.org/10.1117/12.2176174

KEYWORDS: Wavefront sensors, Wavefronts, Cameras, Profiling, Reconstruction algorithms, Inspection, Semiconducting wafers, Sensing systems, Collimators, Prisms

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Proceedings Article | 14 November 2013 Paper

Predictive growth model of LID: light intensification model

ChingSeong Tan, D. Patel, X. Wang, D. Schlitz, P. S. Dehkordi, C. Menoni, E. Chong

Proceedings Volume 8885, 88850A (2013) https://doi.org/10.1117/12.2030291

KEYWORDS: Laser induced damage, Absorption, Backscatter, Light scattering, Ionization, Chemical species, Scattering, Crystals, Monte Carlo methods, Convolution

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Proceedings Article | 30 September 2013 Paper

Range reconstruction model for 3D gated imaging

ChingSeong Tan, TongYuen Chai, SingYee Chua, Xin Wang, BokMin Goi, Gerald Seet

Proceedings Volume 8842, 88420R (2013) https://doi.org/10.1117/12.2022812

KEYWORDS: 3D modeling, 3D image processing, Pulsed laser operation, Cameras, 3D image reconstruction, Gated imaging, Imaging systems, Image acquisition, Volume rendering, Remote sensing

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Proceedings Article | 28 September 2013 Paper

Performance evaluation of hybrid VLC using device cost and power over data throughput criteria

C. C. Lee, C. S. Tan, H. Y. Wong, M. B. Yahya

Proceedings Volume 8845, 88451A (2013) https://doi.org/10.1117/12.2025386

KEYWORDS: Light emitting diodes, Digital signal processing, Standards development, Computer architecture, Visible radiation, Data transmission, Data communications, Systems modeling, Multimedia, System integration

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Proceedings Article | 22 June 2013 Paper

Gated imaging for multi-layer wave-front sensing and surface reconstruction

ChingSeong Tan, Xin Wang, Wee Keong Lim, Yong Han Ng, Tong Yuen Chai

Proceedings Volume 8769, 87690B (2013) https://doi.org/10.1117/12.2020845

KEYWORDS: Semiconducting wafers, Wavefront sensors, Wavefronts, Gated imaging, Cameras, Semiconductor manufacturing, Silicon, Reconstruction algorithms, Manufacturing, Wave propagation

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SPIE Journal Paper | 1 November 2005

Model of gated imaging in turbid media

Ching Tan, Andrzej Sluzek, Gerald Seet

OE, Vol. 44, Issue 11, 116002, (November 2005) https://doi.org/10.1117/12.10.1117/1.2124567

KEYWORDS: Backscatter, Interference (communication), Signal to noise ratio, Cameras, Image quality, Signal attenuation, Gated imaging, Receivers, Monte Carlo methods, Imaging systems

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Proceedings Article | 12 April 2005 Paper

Quantitative image quality evaluations of enhanced images in turbid water medium

Gerald Seet, Andrzej Sluzek, ChingSeong Tan

Proceedings Volume 5852, (2005) https://doi.org/10.1117/12.621413

KEYWORDS: Image quality, Image enhancement, Imaging systems, Image processing, Scattering, Underwater imaging, Modulation transfer functions, Image fusion, Ocean optics, Visibility

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Proceedings Article | 8 August 2003 Paper

Practical quantitative assessment of imaging system in turbid water using a modified fidelity index

Ching Tan, Gerald Seet, Andrzej Sluzek

Proceedings Volume 5108, (2003) https://doi.org/10.1117/12.488942

KEYWORDS: Image quality, Imaging systems, Scattering, Underwater imaging, Interference (communication), Cameras, Quality measurement, Image processing, Visual process modeling, Signal to noise ratio

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Images associated with Underwater Imaging Systems are frequently degraded due to absorption and scattering effects from its underwater environment. The absorption effect reduces the signal strength, and the latter effect reduces both signal strength and image resolution. The optimization of underwater imaging system parameters predominantly focuses on maximizing signal strength and minimizes scattering effects. In the domain of underwater images, the assessment of image quality is highly subjective and lacks the availability of a "standard" objective criteria, which allows a comparison of different imaging techniques and their effectiveness to be performed in a more objective manner. This paper focuses on an experimental performance evaluation of underwater imaging system through objective image quality measurement. The technique is based on 2 dimensional grayscale image of USAF (United State Air Force) target. These targets have been used extensively in underwater imaging system development. It has resolution bars in various frequencies and arrangement, which enable spatial frequencies and signal strength analysis. 3 different image evaluation techniques are used to quantify image quality of an Underwater Imaging System in increased turbidity condition. Peak Signal to Noise Ratio (PSNR) measures the output signal over its Mean Square Error (MSE). Fidelity, F, represents the absolute difference of amplitude values and the Correlation coefficient, r, reflects only changes of signal shape. The metrics scales are considered as a measure of similarity between the idealized and the derived image. In these techniques, the indices are applied to corresponding pixels of the derived and ideal images. The fidelity, F and correlation coefficient, r are applied to thermal imaging evaluation by Volodymyr Borovytsky and Valery Fesenko in 2000. The underwater images have similar characteristics to that from thermal imaging system. There is a significant component of random noise effects (from background or environments) degrading the original signal to be captured by the camera. Test conditions and processes may also induce unwanted errors or distortions into the measurement of the image quality. These include camera movement, light intensity and lens zoom. The sensitivity of some of these effects on the indexes are also presented. Some modifications of the evaluation techniques are proposed. The Modified Fidelity, MF is linearly correlated with the image quality (scattering effects) of the testing images compared to the other methods. Hence, MF is a suitable measure to quantify the scattering effect of underwater images.

Showing 5 of 9 publications

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