Byeungwoo Jeon

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Papers by Byeungwoo Jeon

Ray-Space Motion Compensation for Lenslet Plenoptic Video Coding

arXiv (Cornell University), Jul 1, 2022

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User-Priority Based AV1 Coding Tool Selection

IEEE Transactions on Broadcasting, Sep 1, 2021

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A New Scheme for Essential Protein Identification Based on Uncertain Networks

IEEE Access, 2020

Identifying essential proteins is important for not only understanding cellular activity but also... more Identifying essential proteins is important for not only understanding cellular activity but also detecting human disease genes. A series of centrality measures have been proposed to identify essential proteins based on the protein-protein interaction (PPI) network. Although, existing studies have focused on the topological features of the PPI network and the intrinsic characteristics of biological attributes. it is still a big challenge to further improve the prediction accuracy of essential proteins. Moreover, there are substantial amounts of false-positive data in PPI networks; thus, a PPI network should be modelled as an uncertain network. How to identify essential proteins more accurately and conveniently has become a research hotspot. In this paper, we proposed a new essential protein discovery method called ETB-UPPI on uncertain PPI networks. The algorithm detects essential proteins by integrating topological features with biological information. Experimental results on four Saccharomyces cerevisiae datasets have shown that ETB-UPPI can not only improve the prediction accuracy but also outperform other prediction methods, including the most commonly-used centrality measures (DC, SC, BC, IC, EC, and NC), topology-based methods (LAC) and biological-data-integrating methods (PeC, WDC, UDONC, LBCC, TEGS, and RSG).

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Design of Partially Supervised Classifiers for Multispectral Image Data

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Block Compressive Sensing of Image and Video with Nonlocal Lagrangian Multiplier and Patch-based Sparse Representation

arXiv (Cornell University), Mar 15, 2017

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Multi-Target Detection in FMICW Radar Using Machine Learning

The Journal of Korean Institute of Electromagnetic Engineering and Science

561 Ⅰ. 서 론 FMICW(frequency modulated interrupted continuous waveform) 레이다는 광대역 신호 생성이 가능하고, 송수신 차... more 561 Ⅰ. 서 론 FMICW(frequency modulated interrupted continuous waveform) 레이다는 광대역 신호 생성이 가능하고, 송수신 차 폐 구조로 고출력 신호를 송수신할 수 있어 장거리에서 고해상도 파형이 필요할 때 사용된다 [1]∼[3] . 일반적으로 FMICW 시스템은 FMCW(frequency modulated continuous waveform)와 유사하게 송신주파수와 수신주파수의 차이  *성균관대학교 전자전기컴퓨터공학과(Department of Electrical and Computer Engineering, Sungkyunkwan University) **한화시스템 특수레이다팀(Specific Radar Team, Hanwha Systems) ***한국과학기술원 전기 및 전자공학부(School of Electronic Engineering, KAIST) ․Manuscript

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Refocusing Metric of Light Field Image Using Region-Adaptive Multi-Scale Focus Measure

IEEE Access

Compared with conventional photography, the newly emerging light field image capturing technique ... more Compared with conventional photography, the newly emerging light field image capturing technique has dramatically extended potential capabilities of post processing. Among the new capabilities, refocusing is of the most interest. In this paper, we first investigate a region-adaptive multi-scale focus measure (RA-MSFM) that is able to more robustly and accurately measure focus of light field images. It is especially superior when measuring focus in flat areas where previous methods struggle. Following we design a novel refocusing measure metric which employs the RA-MSFM as core technique. Using the metric, refocusing capability of a given light field image as a whole can be measured in a single number by combining focus score maps of each refocused image in the focal stack. The focus score maps are generated using the proposed RA-MSFM. In RA-MSFM, different multi-scale factor is adaptively selected depending on different regions such as texture-rich or flat areas using a multi-layer perceptron network. Different from most light field image metrics that assess image quality, our metric targets to assess refocusing capability. Our experiments have shown that not only does the proposed refocusing metric have high correlation with subjective evaluations given in the form of mean opinion scores, but it also produces all-in-focus images having 0.7 ∼ 4.6dB higher PSNRs compared to previous state-of-the-art methods. The proposed refocusing metric can be used to measure refocusing loss in practical application such as compression, tone mapping, denoising, and smoothing. 17 18 an LF image can be thought as the overall degree of focusing 48 in the images refocused at arbitrary points. There has been 49 research on focus measurement, however, it is noted that 50 most focus measures [10], [11], [12], [13], [14] were only 51 developed with general 2D images in mind, and there are only 52 a few studies [15], [16], [18] that have looked at refocusing 53 of light field images. The motivation and contribution of this 54 paper is to design a measure of general refocusing capability 55 of light field images. 56 Focus measures (FM) are widely used for many problems 57 of image processing and computer vision, such as for depth 58 from focus [15], [16], [20], autofocus [18]. The existing FM 59 operators for conventional 2D images can be divided into two 60 main categories: spatial domain FM and frequency domain 61 FM [8]. The operators and their advantages are listed in 62 Table 1. There are roughly four families of spatial domain 63 focus measures: Gradient-based, Laplacian-based, statistics-64 based, and the rest. The analysis and ranking results of FM 65 operators [9] shows that the modified Laplacian (LAP2) 66 [10], tenengrad of gradient variance (GRA7) [11], eigenvalue 67 based (STA2) [3], and image contrast (MIS3) [14] methods 68 achieve the overall high performance among the four fam-69 ilies. Noise robustness tests in [9] indicate that STA2 and 70 GRA7 methods handle noise very well. 71 However, it should also be noted that there are a few FM 72 methods that have been developed for LF images. Surh [15] 73 proposed a FM employing a ring difference filter (RDF) 74 which maintains high robustness and confidence by utilizing 75 a relatively large window of neighboring pixels and placing a 76 ring gap space to ignore certain regions in that window. The 77 RDF focus measure is especially useful in depth estimation 78 for LF images. Rizkallah [17] proposed a metric to decide 79 whether a certain pixel in a focal stack is in focus or not by 80 thresholding of pixel gradient. This metric is used to evaluate 81 compression loss by counting the number of in-focus pixels. 82 It is a very simple metric which judges whether a pixel is 83 in-focus or not by hard thresholding on gradient value, but 84 101386 VOLUME 10, 2022 mainly describes the proposed focal-stack oriented refocus-132 ing measure methodology of which the RA-MSFM is a core 133 part. Section III shows the overall structure, flowchart, and 134 the procedure optimization. Section IV presents experiments 135 and analysis, including the all-in-focus rendering experi-136 ment and two subjective experiments. The all-in-focus ren-137 dering experiment and one of the subjective experiments 138 on focus level are used to evaluate RA-MSFM. The other 139 subjective experiment on in-focus pixel coverage is used 140 to evaluate the refocusing metric. Section V concludes the 141 paper. 142 II. PROPOSED REFOCUSING MEASURE METHODOLOGY 143 In this Section, we present the proposed RA-MSFM and a 144 new refocusing measure metric. The proposed RA-MSFM 145 not only works well with high frequency rich textures, but 146 also achieves good performance in the in-focus flat areas 147 meanwhile being robust to noise. Using the proposed refo-148 cusing metric, we can compute a single value representing 149 overall degree of focusing on a refocused image generated by 150 post processing of LF image. 151 A. PROPOSED REGION-ADAPTIVE MULTI-SCALE FOCUS 152 MEASURE (RA-MSFM) 153 A focus map is a collection of focus levels of pixels in an 154 image. The focus level indicates how much in-focus a given 155 pixel is. A higher focus level indicates that the pixel has the 156 better focus. By conventional methods [9], [18], the focus 893 894

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User-Priority Based AV1 Coding Tool Selection

IEEE Transactions on Broadcasting, 2021

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Deinterlacing apparatus and method capable of outputting two consecutive deinterlaced frames

Spatio-temporal contextual classification of remotely sensed multispectral data

IEEE International Conference on Systems, Man, and Cybernetics, 1990

A spatio-temporal contextual classifier that can utilize both spatial and temporal information is... more A spatio-temporal contextual classifier that can utilize both spatial and temporal information is investigated. Experiments carried out with Landsat TM data are reported. They show that spatial correlation contexts are more useful than the other contexts. The use of the homogeneity test followed by a selective application of the contextual rule is more effective than the totally recursive case in

Digital Video Scrambling Method Using Intra Prediction Mode

Lecture Notes in Computer Science, 2004

As the amount of digitalized contents increases rapidly, &amp;amp;amp;amp;amp;amp;amp;amp;amp... more As the amount of digitalized contents increases rapidly, &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;se- curity&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; necessarily arises as one of the most important issues. The main distribution channel of digital contents is Internet which is very easily accessible. Therefore content protection becomes a major issue as impor- tant as data coding techniques. In recent years, many developers have studied techniques that allow only authorized person

Fast implementation of Wyner-Ziv Video codec using GPGPU

2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 2010

In this paper, we report a fast implementation of Wyner-Ziv video decoder using general-purpose c... more In this paper, we report a fast implementation of Wyner-Ziv video decoder using general-purpose computing on graphics processing units (GPGPU). Despite of its many advantages, Wyner-Ziv video coding has a problem of huge decoding complexity. Since Slepian-Wolf decoding with rate adaptive LDPC accumulate code takes up more than 90% of entire Wyner-Ziv video decoding complexity, in this paper, we focus on fast implementation of the Slepian-Wolf decoder using the CUDA (Compute Unified Device Architecture) which is a GPGPU architecture developed by NVIDIA. Our implementation is shown to be 4~5 times (QCIF size) or 15~20 times (CIF size) faster compared to conventional Slepian-Wolf decoding.

Low complexity video enhancement of video phone calls with a limited mobile terminal's capability

ABSTRACT

HVS based iterative hard thresholding recovery for compressive sensed image

Iterative hard thresholding (IHT) is a technique popularly used in compressive sensing recovery. ... more Iterative hard thresholding (IHT) is a technique popularly used in compressive sensing recovery. Human eyes have different sensitivity depending on frequency, thus, errors in low frequency affects human perception more seriously than in high frequency. However, IHT treats all transformed coefficients equally without differentiating their visual sensitivity. This paper proposes an improved IHT scheme based on human visual sensitivity by using a weighting process. Visually significant coefficients are emphasized more by large weights before the hard thresholding. Experimental results show its superiority over conventional IHT in both objective and subjective qualities.

Design of partially supervised classifiers for multispectral image data

This report addresses a partially supervised classification problem, especially when the class de... more This report addresses a partially supervised classification problem, especially when the class definition and corresponding training samples are provided a pnori only for just one particular class. In practical applications of pattern classification techniques, a frequently observed characteristic is the heavy, often nearly impossible requirements on representative prior statistical class characteristics of all classes in a given data set. Considering the effort in both time and man-power required to have a well-defined, exhaustive list of classes with a corresponding representative set of training samples, this "partially" supervised capability would be very desirable, assuming adequate classifier performance can be obtained. Two different classification algorithms are developed to achieve simplicity in classifier design by reducing the requirement of prior statistical information without sacrificing significant classifying capability. The first olne is based on optimal significance testing, where the optimal acceptance probability is estimated directly from the data set. In the second approach, the partially supervised classification is considered as a problem of unsupervised clustering with initially one known cluster or class. A weighted unsupervised clustering procedure is developed to automatically define other classes and estimate their class statistics. The operational simplicity thus realized should makes these partially supervised classification schemes very viable tools in pattern classification. This automatic estimation of the proper acceptance probability will be doubtlessly desirable, at least to the user with little prior knowledge about the data set. The algorithm to be proposed in this chapter can also be applied to the case where the specific class of interest consists of several sub-classes. When there are a large number of constituent sub-classes of the given class of interest and the sample distributions of the sub-classes are quite different from each other, this automatic estimation capability should be very handy, since one

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Apparatus and method for controlling variable bit rate in real time

Fast inter mode selection for H.264/AVC using large block and zero motion consistency history

TENCON 2007 - 2007 IEEE Region 10 Conference, 2007

To achieve high coding efficiency, the new H.264/AVC standard developed more advanced coding tool... more To achieve high coding efficiency, the new H.264/AVC standard developed more advanced coding tools than previous standards such as powerful prediction techniques and rate-distortion optimization. Although it can achieve high coding efficiency, it requires huge computation. To reduce the complexity, we propose a fast inter mode selection with early P8x8 mode rejection and early 16x16 block size detection by referring

Digital Watermarking

Lecture Notes in Computer Science, 2008

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<title>Rotation-, scaling-, and translation-robust image watermarking using Gabor kernels</title>

Security and Watermarking of Multimedia Contents IV, 2002

ABSTRACT

Hierarchical motion search for H.264 variable-block-size motion compensation

Optical Engineering, 2006

Compared to conventional video standards, the main features of H.264 standard are its high coding... more Compared to conventional video standards, the main features of H.264 standard are its high coding efficiency and its network friendliness. In spite of these outstanding merits, it is not easy to implement H.264 codec as a real-time system, due to its requirements of large memory bandwidth and intensive computation. Although the variable-block-size motion compensation using multiple reference frames is one

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