• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.25-33
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• 2007

In this paper, I propose a method which can enhance the visual quality of IRST images based on a loaded location in ship and an AOS. The IRST adjusts an AOS to detect targets with various altitudes because of its narrow vertical field of view and offers various functions to enhance images with its low contrast. In the proposed method, images are divided into two regions of sea and sky on the basis of the horizon after establishing relation between an AOS and a horizon location within an image. As a result, image enhancement of the proposed method is performed adaptively according to the divided region while that of conventional method is performed for entire image without the region division. Simulation results show that the proposed method represents higher visibility compared with conventional one.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.260-264
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• 2013

This paper proposes a fast enhancement layer coding method to reduce computational complexity for Scalable HEVC (SHVC) which is based on High Efficiency Video Coding (HEVC). The proposed method decreases encoding time by simplifying Rate Distortion Optimization (RDO)for enhancement layers (EL). The simplification is achieved by restricting CU depths based on the correlation of coding unit (CU) depths between adjacent layers and scalability (spatial or quality) of EL. Comparing with the performance of SHM 1.0 software encoder, the proposed method reduces the encoding time by up to 31.5%.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.911-921
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• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.

• Asian Journal of Atmospheric Environment
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• v.3 no.1
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• pp.1-8
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• 2009

Enhancement of aerosol optical thickness (AOT) and surface aerosol mass concentration in Korea for an active forest fire episode in Northeast Asia were estimated by Community Multi-scale Air Quality (CMAQ) model. MODIS/TERRA remote detects of fires in Northeast Asia for May 2003 gave a constraint for estimation of wildfire emissions with an NDVI distribution for recent five years. The simulated wildfire plumes and enhancement of AOT were evaluated and well resolved by comparing multiple satellite observations such as MODIS, TOMS, and others. Scatter plots of observed daily mean aerosol extinction coefficient versus $PM_{10}$ concentration in ground level in Korea showed distinctively different trends based on the ambient relative humidity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.39-44
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• 2004

The three-dimensional (3D) wavelet transform with motion compensation is suitable for very high quality video coding due to both spatial and temporal decorrelations. However, it still suffers from image degradation such as ringing artifact and afterimage because of the loss of high frequency components by quantization. This paper proposes an iterative regularized enhancement of the motion-compensated 3D wavelet coded video. We also propose the adaptive implementation of the constraints for the regularization. It selectively suppresses the high frequency component along only the corresponding edge direction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.70-75
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• 2007

In order to mitigate the problems in storage space and network bandwidth for the full CD quality audio with 44.1 kHz sampling rate, current existing digital audio is always restricted by sampling rate and bandwidth. This kind of restriction normally can be resolved by using low bit rate audio codec such as MP3, OGG, and AAC. However it suffers a major problem such as a loss of high frequency fidelity. This high frequency loss will reproduce only the band-limited low-frequency part of audio in the standard CD-quality audio. In general, the high frequency contents of audio have lots of information such as localization and ambient information, and bright nature of audio. The purpose of this paper is to implement on ARM platform system that can effectively estimate and compensate the missing high frequency contents of MP3 audio. From the experimental results with spectrum analysis and listening test, we confirm the superiority of the proposed algorithms for MP3 audio quality enhancement.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.453-467
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• 2014

A typical histogram equalization contrast enhancement effect for improving the image quality is excellent. However, because it appears that excessive changes of the brightness values, The average brightness of the image is changing in units of frames of applications such as a TV video is unsuitable. In order to solve these drawbacks, a modified method of histogram equalization on various studies have been made. But the result images of existing methods sometimes shown visual degradations such as over-enhancement and false contouring. In this paper, we propose improved contrast enhancement method through bi-histogram equalization using target mean brightness based on differential compression method. The proposed method is based on the average brightness value by dividing the histogram, the histogram for each zone, according to the frequency differential of compression. And equalize the modified histogram based on target mean brightness. This allows to suppress deterioration of picture quality, and changes in the average brightness of each frame of video, while maintaining and improving the contrast. Experimental results show that the proposed method compared to the conventional method, the average brightness of each frame from a movie well maintained, and no degradation of the image quality showed a good effect to improve the contrast.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.87-96
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• 2007

In this paper we propose a new noise reduction algorithm for stationary and nonstationary noisy environments. Our algorithm classifies the speech and noise signal contributions in time-frequency bins, and is not based on a spectral algorithm or a minimum statistics approach. It relies on calculating the ratio of the standard deviation of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. We show that good quality can be achieved for enhancement speech signal by choosing appropriate values for ${\delta}_t\;and\;{\delta}_f$. The proposed method greatly reduces the noise while providing enhanced speech with lower residual noise and somewhat higher mean opinion score (MOS), background intrusiveness (BAK) and signal distortion (SIG) scores than conventional methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.85-88
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• 2011

This paper describes a single channel speech enhancement as the pre-processor of automatic speech recognition system. The improvements are based on using optimally modified log-spectra (OM-LSA) gain function with a non-causal a priori signal-to-noise ratio (SNR) estimation. Experimental results show that the proposed method gives better perceptual evaluation of speech quality score (PESQ) and lower log-spectral distance, and also better word accuracy. In the enhancement system, parameters was turned for automatic speech recognition.

• Journal of the Korean Magnetic Resonance Society
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• v.15 no.2
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• pp.157-174
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• 2011

Although the use of apodization functions in connection with postprocessing of a 2D NMR spectrum proves improved spectral quality, there is usually a trade-off between resolution enhancement and noise suppression due to a classical "uncertainty principle." In this study, therefore, a mathematical deconvolution technique called "Maximum Likelihood Deconvolution (MLD)" was adopted to achieve the spectral resolution and sensitivity enhancement simultaneously. The MLD technique greatly facilitates visualization and restoration of the genuine spectral information from complex 2D NMR spectra that would be problematic with the conventional apodization/FT processing. In particular, application of the MLD to the 2D-NOE spectrum would be very useful to derive the important proton connectivities, which are essential to achieve elucidating the 3D molecular structure.