• ETRI Journal
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• v.36 no.4
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• pp.591-598
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• 2014

This paper proposes a new min-sum algorithm for low-density parity-check decoding. In this paper, we first define the negative and positive effects of the received signal-to-noise ratio (SNR) in the min-sum decoding algorithm. To improve the performance of error correction by considering the negative and positive effects of the received SNR, the proposed algorithm applies adaptive scaling factors not only to extrinsic information but also to a received log-likelihood ratio. We also propose a combined variable and check node architecture to realize the proposed algorithm with low complexity. The simulation results show that the proposed algorithm achieves up to 0.4 dB coding gain with low complexity compared to existing min-sum-based algorithms.

• Journal of The Korean Astronomical Society
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• v.52 no.2
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• pp.49-55
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• 2019

The New Vacuum Solar Telescope (NVST) is the largest solar telescope in China. When using CCDs for imaging, equal-thickness fringes caused by thin-film interference can occur. Such fringes reduce the quality of NVST data but cannot be removed using standard flat fielding. In this paper, a correction method based on multi-scale decomposition and adaptive partitioning is proposed. The original image is decomposed into several sub-scales by multi-scale decomposition. The region containing fringes is found and divided by an adaptive partitioning method. The interference fringes are then filtered by a frequency-domain Gaussian filter on every partitioned image. Our analysis shows that this method can effectively remove the interference fringes from a solar image while preserving useful information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.341-357
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• 2010

Forward Error Correction (FEC) techniques have been adopted to overcome packet losses and to improve the quality of video delivery. The efficiency of the FEC has been significantly compromised, however, due to the characteristics of the wireless channel such as burst packet loss, channel fluctuation and lack of Quality of Service (QoS) support. We propose herein an Adaptive Cross-layer FEC mechanism (ACFEC) to enhance the quality of video streaming over 802.11 WLANs. Under the conventional approaches, FEC functions are implemented on the application layer, and required feedback information to calculate redundancy rates. Our proposed ACFEC mechanism, however, leverages the functionalities of different network layers. The Automatic Repeat reQuest (ARQ) function on the Media Access Control (MAC) layer can detect packet losses. Through cooperation with the User Datagram Protocol (UDP), the redundancy rates are adaptively controlled based on the packet loss information. The experiment results demonstrate that the ACFEC mechanism is able to adaptively adjust and control the redundancy rates and, thereby, to overcome both of temporary and persistent channel fluctuations. Consequently, the proposed mechanism, under various network conditions, performs better in recovery than the conventional methods, while generating a much less volume of redundant traffic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1201-1207
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• 2006

In this paper, we say the adaptive shading correction system supporting multi-resolution for mobile camera. The shading effect is caused by non-uniform illumination, non-uniform camera sensitivity, or even dirt and dust on glass (lens) surfaces. In general this shading effect is undesirable [1-3]. Eliminating it is frequently necessary for subsequent processing and especially when quantitative microscopy is the fine goal. The proposed system is available on thirty nine kinds of image resolutions scanned by interlaced and progressive type. Moreover, the system is using forty kinds of continuous quadratic equations instead of using the piece-wise linear curve which is composed of multiple line segments. Finally, the system could correct the shading effect without discontinuity in any image resolution. The proposed system is implemented in VLSI with cell library based on Hynix $0.25{\mu}m$ CMOS technology.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.18-26
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• 2015

Geometric distortion and shadow effect due to capturing angle could be included in document copy images that are captured by a camera in stead of a scanner. In this paper, a clean black and white document image generation algorithm by distortion correction and shadow elimination based on a camera, is proposed. In order to correct geometric distortion such as straightening un-straight boundary lines occurred by camera lens radial distortion and eliminating outlying area included by camera direction, second derivative filter based document boundary detection method is developed. Black and white images have been generated by adaptive binarization method by eliminating shadow effect. Experimental results of the black and white document image generation algorithm by recovering geometrical distortion and eliminating shadow effect for the document images captured by smart phone camera, shows very good processing results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.453-461
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• 2012

This paper proposes an improved phase estimation method for AM(Amplitude Modulation) range measurement system. The previous phase estimation method induces errors by Doppler shift of a moving target. The proposed method compensates phase estimation error through the ADC(Adaptive Doppler Correction) to take the Doppler shift, thus can improve distance measurement accuracy. When compared with the previous method through simulation results, the Doppler shift compensation and accuracy are improved by 94.7% and 50%, respectively. Target distance error in an acoustic tank is estimated to be 7.7cm, which confirms that the proposed method can be used to estimate the distance in the marine environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.6
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• pp.540-549
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• 2013

An adaptive non-uniform quantization scheme is proposed for soft-decision error correction in NAND flash memory. Even though the conventional maximizing mutual information (MMI) quantizer shows the optimal post-FEC (forward error correction) bit error rate (BER) performance, this quantization scheme demands heavy computational overheads due to the exhaustive search to find the optimal parameter values. The proposed quantization scheme has a simple structure that is constructed by only six parameters, and the optimal values of them are found by maximizing the mutual information between the input and the output symbols. It is demonstrated that the proposed quantization scheme improves the BER performance of soft-decision decoding with only small computational overheads.

• Current Optics and Photonics
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• v.2 no.6
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• pp.612-622
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• 2018

In wave-front-sensor-less adaptive optics (WFS-less AO) systems, the Jacopo Antonello (JA) method belongs to the model-based class and requires few iterations to achieve acceptable distortion correction. However, this method needs a lot of measurements, especially when it deals with moderate or severe aberration, which is undesired in free-space optical communication (FSOC). On the contrary, the stochastic parallel gradient descent (SPGD) algorithm only requires three time measurements in each iteration, and is widely applied in WFS-less AO systems, even though plenty of iterations are necessary. For better and faster compensation, we propose a WFS-less hybrid approach, borrowing from the JA method to compensate for low-order wave front and from the SPGD algorithm to compensate for residual low-order wave front and high-order wave front. The correction results for this proposed method are provided by simulations to show its superior performance, through comparison of both the Strehl ratio and the convergence speed of the WFS-less hybrid approach to those of the JA method and SPGD algorithm.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.95-103
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• 2017

Horizon correction is a crucial stage for image composition enhancement. In this paper, we propose a deep learning based method for estimating the slanted angle of a photograph and correcting it. To estimate and correct the horizon direction, existing methods use hand-crafted low-level features such as lines, planes, and gradient distributions. However, these methods may not work well on the images that contain no lines or planes. To tackle this limitation and robustly estimate the slanted angle, we propose a convolutional neural network (CNN) based method to estimate the slanted angle by learning more generic features using a huge dataset. In addition, we utilize multiple adaptive spatial pooling layers to extract multi-scale image features for better performance. In the experimental results, we show our CNN-based approach robustly and accurately estimates the slanted angle of an image regardless of the image content, even if the image contains no lines or planes at all.

• Journal of KIISE:Information Networking
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• v.30 no.6
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• pp.755-763
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• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.