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Wonha Kim

Kyung Hee University · 情報科学

研究室紹介

Professor Wonha Kim's research lab specializes in advanced image and video processing, with a strong focus on perceptual quality optimization, efficient signal representation, and robust coding techniques. The lab explores innovative methods in dehazing, subband and wavelet-based coding, radial image processing, and entropy-constrained quantization, all aimed at enhancing visual fidelity while minimizing computational complexity. Key research directions include perceptual video coding, geometric image modeling, and joint optimization of transform, quantization, and entropy coding for high-performance image and video compression. The lab emphasizes the integration of human visual perception with signal processing algorithms to achieve superior visual quality under constrained bitrates and implementation resources.

image dehazingperceptual video codingsubband codingentropy-constrained quantizationwavelet-based coding

Research Overview

Papers
91
Total Citations
448
Papers (5y)
9
Primary Field
情報科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
9total
2022
2023
2024
2025
2026
Citations per year (5y)
16total
20222023202420252026

Selected Papers

15
1
Article|243 citations·2017
Single Image Dehazing Using Color Ellipsoid Prior
Trung Minh Bui, Wonha Kim
SJR Q1IEEE Transactions on Image Processing

In this paper, we propose a new single-image dehazing method. The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry. The transmission values generated by the proposed method maximize the contrast of dehazed pixels, while preventing over-saturated pixels. The values are also statistically robust because they are calculated from the averages of the haze pixel val

Computer Vision and Pattern RecognitionComputer Science
2
Article|34 citations·2012
Video Processing for Human Perceptual Visual Quality-Oriented Video Coding
Hyung‐Suk Oh, Wonha Kim
SJR Q1IEEE Transactions on Image Processing

We have developed a video processing method that achieves human perceptual visual quality-oriented video coding. The patterns of moving objects are modeled by considering the limited human capacity for spatial-temporal resolution and the visual sensory memory together, and an online moving pattern classifier is devised by using the Hedge algorithm. The moving pattern classifier is embedded in the existing visual saliency with the purpose of providing a human perceptual video quality saliency mod

Computer Vision and Pattern RecognitionComputer Science
3
Article|23 citations·2015
Respiratory Health Risks for Children Living Near a Major Railyard
Rhonda Spencer-Hwang, Sam Soret, Synnøve F. Knutsen, David Shavlik, Mark Ghamsary, W. Lawrence Beeson, Wonha Kim, Susanne Montgomery
SJR Q1Journal of Community Health
Health, Toxicology and MutagenesisEnvironmental Science
4
Article|11 citations·2012
Immunology and Allergy
Wonha Kim
Elsevier eBooks
ImmunologyImmunology and Microbiology
5
Article|6 citations·1998
Wavelet-based image coder with entropy-constrained lattice vector quantizer (ECLVQ)
Wonha Kim, Yu Hen Hu, T.Q. Nguyen
IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing

This paper presents an algorithm that jointly optimizes a lattice vector quantizer (LVQ) and an entropy coder in a subband coding at all ranges of bit rate. Estimation formulas for both entropy and distortion of lattice quantized subband images are derived. From these estimates, we then develop dynamic algorithm optimizing the LVQ and entropy coder together for a given entropy rate. Compared to previously reported min-max approaches, or approaches using asymptotic distortion bounds, the approach

Computer Vision and Pattern RecognitionComputer Science
6
Article|5 citations·1998
Adaptive wavelet packet based image coding with optimal entropy-constrained lattice vector quantizer (ECLVQ)
Wonha Kim, Thi-Oanh Nguyen, Yu Hen Hu
SJR Q1IEEE Transactions on Signal Processing

In this work, wavelet basis and source coding are jointly optimized, while specifying the source coding strategy as entropy-constrained lattice vector quantizer (ECLVQ). The presented approach differs from previous works in which the choice of wavelet basis is quasioptimal, but the quantizer set is optimally chosen.

Computer Vision and Pattern RecognitionComputer Science
7
Article|3 citations·2024
Image Processing in L1-Norm-Based Discrete Cartesian and Polar Coordinates
Geunmin Lee, Wonha Kim
SJR Q2ElectronicsOA

This paper proposes a radial image processing method performed in an L1-norm-based discrete polar coordinate system. For this purpose, we address the problem that polar coordinates based on the L2-norm cannot exist in discrete systems and then develop a method for converting Cartesian coordinates to L1-norm-based discrete polar coordinates. The proposed method greatly reduces the directional variance occurring in the Cartesian coordinate system and so processes radial directional images along th

Computer Vision and Pattern RecognitionComputer Science
8
Article|2 citations·2002
Wavelet packet based optimal subband coder
Wonha Kim, Yu Hen Hu

Proposes an algorithm to use in designing a subband coder (SBC) constructed by wavelet packet, to achieve minimum distortion for a given bit budget and implementation complexity. The authors map the QMF tree structures onto a binary tree, then formulate the task as an optimization problem including coding bit and implementation complexity constraints. The problem is dissected into two phases. First, they derive the optimal bit allocation strategy which covers the entire range of bit rate, and se

Computer Vision and Pattern RecognitionComputer Science
9
Article|2 citations·2021
DCT Domain Detail Image Enhancement for More Resolved Images
Seongbae Bang, Wonha Kim
SJR Q2ElectronicsOA

This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy i

Computer Vision and Pattern RecognitionComputer Science
10
Article|1 citations·2006
Scalable Interframe Wavelet Coding with Low Complex Spatial Wavelet Transform
Wonha Kim, Seyoon Jeong, Kyuheon Kim
SJR Q2ETRI JournalOA

In the decoding process associated with interframe wavelet coding, the inverse wavelet transform requires high computational complexity. However, as video technology starts to pervade all aspects of our lives, decoders are becoming required in various devices such as PDAs, notebooks, PCs, and set-top boxes. Therefore, a decoder's complexity needs to be adapted to the processor's computational power, and consequently a low-complexity codec is also required for scalable video coding. In this paper

Computer Vision and Pattern RecognitionComputer Science
11
Article|1 citations·2008
HOMOGENEIYT AND RANKLET BASED MASS-TYPE CANCER DETECTION IN DENSE MAMMOGRAPHIC IMAGES
Wonha Kim, Sung-Min Kim
Artificial IntelligenceComputer Science
12
Article|1 citations·2006
Scalable Interframe Wavelet Coding with Low Complex Spatial Wavelet Transform
김원하, Seyoon Jeong, 김규헌

In the decoding process associated with interframe wavelet coding, the inverse wavelet transform requires high computational complexity. However, as video technology starts to pervade all aspects of our lives, decoders are becoming required in various devices such as PDAs, notebooks, PCs, and set-top boxes. Therefore, a decoder's complexity needs to be adapted to the processor's computational power, and consequently a lowcomplexity codec is also required for scalable video coding. In this paper,

13
Article|1 citations·1997
<title>Joint optimization of lattice vector quantizer and entropy coder in subband coding</title>
Wonha Kim, Yu Hen Hu, Truong Q. Nguyen
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

This paper presents an algorithm that jointly optimizes a lattice vector quantizer (LVQ) and an entropy coder in a subband coding at all ranges of bit rate. Estimation formulas for both entropy and distortion of lattice quantized subband images are derived. From these estimates, we then develop dynamic algorithm optimizing the LVQ and entropy coder together for a given entropy rate. Compared to previously reported min-max approaches, or approaches using asymptotic distortion bounds, the approach

Computer Vision and Pattern RecognitionComputer Science
14
Article|0 citations·2006
운전자가 졸면 깨워주는 자동차도 등장한다
Wonha Kim
Aerospace EngineeringEngineering
15
Article|0 citations·2018
Fast I-slice encoding and down-scaling from H.264/AVC bit stream
Trung Minh Bui, Duy Huu Le, Saigua Labre Oscar Roberto, Wonha Kim
SJR Q2Journal of Intelligent & Fuzzy Systems

We present a new approach for generating thumbnail images from H.264/AVC coded bit streams. We have verified analytically that mismatch errors between the encoder and decoder prevent the direct generation of thumbnail images from H.264/AVC transform coefficients. Based on this analysis, we have devised a method that exploits both the spatial and transform domains. What distinguishes our algorithm from previous works is that it determines the thumbnail image pixels by summing the residual and est

Signal ProcessingComputer Science

Research Areas

Computer Vision and Pattern RecognitionSignal ProcessingAerospace EngineeringElectrical and Electronic EngineeringArtificial IntelligenceMedia Technology

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