• Title/Summary/Keyword: 예측 디컨볼루션

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Estimation of source signal and channel response using ray-based blind deconvolution technique for Doppler-shifted underwater channel (음선 기반 블라인드 디컨볼루션 기법을 이용한 수중 도플러 편이 채널에서의 송신 신호 및 채널 응답 추정)

  • Byun, Gi Hoon;Oh, Se Hyun;Byun, Sung-Hoon;Kim, J.S.
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.5
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    • pp.331-339
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    • 2016
  • This paper suggests an estimation method of the source signal and the channel impulse response (CIR) using ray-based blind deconvolution (RBD) in the underwater acoustic channel environment where Doppler effect exists by the relative motion between source and receiver. It is difficult to estimate the CIR on Doppler effect by the matched filter with a highly Doppler-sensitive waveform such as the m-sequence signal because Doppler shift can severely degrade the correlation between the received signal corrupted by Doppler effect and the original source signal. In this study, the Doppler-shifted source-signal's phase is estimated using the RBD, and the received signal is compensated by it to obtain the Doppler-corrected CIR. It is verified that using the matched filter with the received signal from the experimental data fails to estimate the CIR while the obtained CIR by the suggested method has the similarity to the propagation path of the ray model. Also, the results show that the reconstructed source signal using the RBD has the better Doppler shift compensation than the Doppler-shifted source signal derived from scattering function.

Identification of Quaternary Faults and shallow gas pockets through high-resolution reprocessing in the East Sea, Korea (탄성파 자료 고해상도 재처리를 통한 동해해역의 제4기 단층 및 천부 가스 인지)

  • Jeong, Mi Suk;Kim, Gi Yeong;Heo, Sik;Kim, Han Jun
    • Journal of the Korean Geophysical Society
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    • v.2 no.1
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    • pp.39-44
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    • 1999
  • High-resolution images are drawn from existing seismic data which were originally obtained by Korea Ocean Research & Development Institute (KORDI) during 1994-1997 for deep seismic studies on the East Sea of Korea. These images are analyzed for mapping Quaternary faults and near-bottom gas pockets. First 12 channels are selected from shot gathers for reprocessing. The processing sequence adopted for high-resolution seismic images comprises data copy, trace editing, true amplitude recovery, common-midpoint sorting, initial muting, prestack deconvolution, bandpass filtering, stacking, highpass filtering, poststack deconvolution, f-x migration, and automatic gain control (AGC). Among these processing steps, predictive deconvolution, highpass filtering, and short window AGC are the most significant in enhancement of resolution. More than 200 Quaternanry faults are interpreted on the migrated sections in the shallow depths beneath the seafloor. Although numerous faults are found mostly at the western continental slope and boundaries of the Ulleung Basin, significant amount of the faults are also indicated within the basin. Many of these faults are believed to be formed with reactivation of basement, from geotectonic activities including volcanism, and often originated in Tertiary, indicating that the tectonic regime of the East Sea might be unstable. Existence of shallow gas pockets casts real hazardous warnings to deep-sea drillings and/or to underwater constructions such as inter-island cables and gas pipelines. On the other hand, discovery of these gas pockets heightens the interests in developing natural resources in the East Sea. Reprocessed seismic sections, however, show no typical seismic characteristics for gas hydrates such as bottom-simulating reflectors in the western continental slope and ocean floor.

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Video Deblurring using Camera Motion Estimation and Patch-wise Deconvolution (카메라 움직임 추정 및 패치 기반 디컨볼루션을 이용한 동영상의 번짐 현상 제거 방법)

  • Jeong, Woojin;Park, Jin Wook;Lee, Jong Min;Song, Tae Eun;Choi, Wonju;Moon, Young Shik
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.12
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    • pp.130-139
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    • 2014
  • Undesired camera shaking can make a blur effect, which causes a degradation of video quality. We propose an efficient method of removing the blur effects on video captured from a single camera. The proposed method has a sequential process that is applied to each frame. The first stage is to estimate the camera motion for each frame. In order to estimate the camera motion, we compute the optical flow using 3 consecutive frames. Then a patch-wise image deconvolution is applied. During the deconvolution, edge prediction is used to improve the quality of image deconvolution. After patch-wise image deconvolution, deblurred patches are integrated into an image to produce a deblurred frame. The above process is performed for each frame. The experimental result shows that the proposed method removes the blur effect efficiently.