Browsing by Author "Chen, Po-Chang"

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A two dimensional partial-response maximum-likelihood technique for holographic data storage systems
(2008-07-01)
Lai, Kuo-Hsin
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Tseng, Chien-Fu
;
Chen, Po-Chang
;
Tarng, Jenn-Hwan
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電信工程研究所
In holographic data storage systems, it is straightforward to increase the storage capacity by mean of reducing the pitches among data symbols. However, this may lead to severe. inter-symbol interference (ISI) and also unacceptable data error rate. To deal with the problem, we first model the channel as a partial response (PR) and use the maximum-likelihood (ML) detection to control the ISI. The Viterbi decoder is employed to implement ML detection.
Digital Image Restoration for Phase-Coded Imaging Systems
(2010)
Tseng, Chen-Yu
;
Wang, Sheng-Jyh
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Chang, Chir-Weei
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Chen, Po-Chang
;
Chang, Chuan-Chung
This paper proposes a digital image restoration algorithm for phase-coded imaging systems. In order to extend the depth-of-field (Dof), an imaging system equipped with a properly designed phase-coded lens can achieve an approximately constant point spread function (PSF) for a wide range of depths. In general, a phase-coded imaging system produces blurred intermediate images and requires subsequent restoration processing to generate clear images. For lowcomputational consumer applications, the kernel size of the restoration filter is a major concern. To fit for practical applications, a pyramid-based restoration algorithm is proposed in which we decompose the intermediate image into the form of Laplacian pyramid and perform restoration over each level individually. This approach provides the flexibility in filter design to maintain manufacturing specification. On the other hand, image noise may seriously degrade the performance of the restored images. To deal with this problem, we propose a Pyramid-Based Adaptive Restoration (PBAR) method, which restores the intermediate image with an adaptive noise suppression module to improve the performance of the phase-coded imaging system for Dof extension.
One-Handed Input Through Rotational Motion for Smartwatches
(2018-01-01)
Tsai, Hsin-Ruey
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Chen, Po-Chang
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Chan, Liwei
;
Hung, Yi-Ping
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資訊工程學系
One-handed input for smartwatches is crucial when users' hands are occupied. A rotational motion is leveraged, which can be detected by built-in motion sensors in most smartwatches, as input to provide item selection. Users control a cursor by rotating the smartwatch into different orientations using the proposed item selection gestures. To understand human wrist dexterity and the ability to perform rotational motion input along each degree of freedom on smartwatches, a human-factor study was performed. Except dexterity, users' consensus and agreement of user-defined rotational motion input gestures for selection and commitment on smartwatches in an exploratory user study were also observed. Based on both the studies, gestures roll and tilt are proposed as selection gestures, and shake and nod are used as commitment gestures. The item selection performance using the proposed gestures in 2D layouts in a user study was further evaluated. The study results showed that tilt-nod and tilt-shake are suitable for item numbers (4x3) and (5x5), respectively. Furthermore, due to high error rate for tilt-shake in (2x2) caused by false positive in shake detection, roll-shake with better social acceptance can be used as an alternative for smartwatches without a built-in front camera in (2x2).