김원하 교수
Wonha Kim
경희대학교 전자공학과 · 컴퓨터과학
연구실 소개
김원하 교수의 연구실은 영상 처리 및 신호 코딩 분야에서 핵심 기술을 개발하고 있습니다. 주요 연구 방향은 환경에 따라 변형되는 환경적 요소(예: 안개)를 보정하는 단일 영상 탈안개 기법, 인간의 시각 인지 특성을 반영한 비디오 코딩 기술, 그리고 웨이블릿 기반 하위대역 코딩과 엔트로피 제약을 고려한 최적의 양자화 기법에 초점이 맞춰져 있습니다. 특히, 인간의 시각적 인지 능력과 신호의 국소적 특성을 융합한 알고리즘 설계가 두드러지며, 실용적 구현과 성능 최적화를 동시에 고려한 연구가 특징입니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15In 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
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
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
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.
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
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
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
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
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,
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
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
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