• Title/Summary/Keyword: 디지털 영상복원

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High-Capacity Reversible Watermarking through Predicted Error Expansion and Error Estimation Compensation (추정 오차 확장 및 오류 예측 보정을 통한 고용량 가역 워터마킹)

  • Lee, Hae-Yeoun;Kim, Kyung-Su
    • The KIPS Transactions:PartB
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    • v.17B no.4
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    • pp.275-286
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    • 2010
  • Reversible watermarking which can preserve the original quality of the digital contents and protect the copyright has been studied actively. Especially, in medical, military, and art fields, the need for reversible watermarking is increasing. This paper proposes a high-capacity reversible watermarking through predicted error expansion and error estimation compensation. Watermark is embedded by expanding the difference histogram between the original value and the predicted value. Differently from previous methods calculating the difference between adjacent pixels, the presented method calculates the difference between the original value and the predicted value, and that increases the number of the histogram value, where the watermark is embedded. As a result, the high capacity is achieved. The inserted watermark is extracted by restoring the histogram between the original value and the predicted value. To prove the performance, the presented algorithm is compared with other previous methods on various test images. The result supports that the presented algorithm has a perfect reversibility, a high image quality, and a high capacity.

A Study on Improvement in Digital Image Restoration by a Recursive Vector Processing (순환벡터처리에 의한 디지털 영상복원에 관한 연구)

  • 이대영;이윤현
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.8 no.3
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    • pp.105-112
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    • 1983
  • This paper discribes technique of the recursive restoration for the images degraded by linear space invariant blur and additive white Gaussian noise. The image is characterized statistically by tis mean and correlation function. An exponential autocorrelation function has been used to model neighborhood model. The vector model was used because of analytical simplicitly and capability to implement brightness correlation function. Base on the vector model, a two-dimensional discrete stochastic a 12 point neighborhood model for represeting images was developme and used the technique of moving window processing to restore blurred and noisy images without dimensionality increesing, It has been shown a 12 point neighborhood model was found to be more adequate than a 8 point pixel model to obtain optimum pixel estimated. If the image is highly correlated, it is necessary to use a large number of points in the neighborhood in order to have improvements in restoring image. It is believed that these result could be applied to a wide range of image processing problem. Because image processing thchniques normally required a 2-D linear filtering.

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Performance Enhancement through Row-Column Cross Scanning in Differential Histogram-based Reversible Watermarking (차이값 히스토그램 기반 가역 워터마킹의 행열 교차 스캐닝을 통한 성능 향상 기법)

  • Yeo, Dong-Gyu;Lee, Hae-Yeoun;Kim, Byeong-Man
    • The KIPS Transactions:PartB
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    • v.18B no.1
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    • pp.1-10
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    • 2011
  • Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved, which enables the restoration of the original media from the watermarked one without any loss of media quality. It has various applications, where high capacity and high visual quality are major requirements. This paper presents a new effective multi-round embedding scheme for the differential histogram-based reversible watermarking that satisfies high capacity requirements of the application. The proposed technique exploits the row-column cross scanning to fully utilize the locality of images when multi-round embedding phase to the message inserted image. Through experiments using multiple kinds of test images, we prove that the presented algorithm provides 100% reversibility, effectiveness of multi-round embedding, and higher visual quality, while maintaining the induced-distortion low.

Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study (딥러닝 알고리즘을 이용한 저선량 디지털 유방 촬영 영상의 복원: 예비 연구)

  • Su Min Ha;Hak Hee Kim;Eunhee Kang;Bo Kyoung Seo;Nami Choi;Tae Hee Kim;You Jin Ku;Jong Chul Ye
    • Journal of the Korean Society of Radiology
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    • v.83 no.2
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    • pp.344-359
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    • 2022
  • Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

A Sub-grid Scale Estimation of Solar Irradiance in North Korea (북한지역 상세격자 디지털 일사량 분포도 제작)

  • Choi, Mi-Hee;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.13 no.1
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    • pp.41-46
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    • 2011
  • Reliable information on the surface solar radiation is indispensable for rebuilding food production system in the famine plagued North Korea. However, transfer of the related modeling technology of South Korea is not possible simply because raw data such as solar radiation or sunshine duration are not available. The objective of this study is restoring solar radiation data at 27 synoptic stations in North Korea by using satellite remote sensing data. We derived relationships between MODIS radiation estimates and the observed solar radiation at 18 locations in South Korea. The relationships were used to adjust the MODIS based radiation data and to restore solar radiation data at those pixels corresponding to the 27 North Korean synoptic stations. Inverse distance weighted averaging of the restored solar radiation data resulted in gridded surfaces of monthly solar radiation for 4 decadal periods (1983-1990, 1991-2000 and 2001-2010), respectively. For a direct application of these products, we produced solar irradiance estimates for each sub-grid cell with a 30 m spacing based on a sun-slope geometry. These products are expected to assist planning of the North Korean agriculture and, if combined with the already prepared South Korean data, can be used for climate change impact assessment across the whole Peninsula.

Fusing Algorithm for Dense Point Cloud in Multi-view Stereo (Multi-view Stereo에서 Dense Point Cloud를 위한 Fusing 알고리즘)

  • Han, Hyeon-Deok;Han, Jong-Ki
    • Journal of Broadcast Engineering
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    • v.25 no.5
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    • pp.798-807
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    • 2020
  • As technologies using digital camera have been developed, 3D images can be constructed from the pictures captured by using multiple cameras. The 3D image data is represented in a form of point cloud which consists of 3D coordinate of the data and the related attributes. Various techniques have been proposed to construct the point cloud data. Among them, Structure-from-Motion (SfM) and Multi-view Stereo (MVS) are examples of the image-based technologies in this field. Based on the conventional research, the point cloud data generated from SfM and MVS may be sparse because the depth information may be incorrect and some data have been removed. In this paper, we propose an efficient algorithm to enhance the point cloud so that the density of the generated point cloud increases. Simulation results show that the proposed algorithm outperforms the conventional algorithms objectively and subjectively.

Digital Watermark Generation Algorithm Embedding Hangul Text (한글 텍스트가 내장된 디지털 워터마크 생성 알고리즘)

  • Cho, Dae-Jea;Kim, Hyun-ki
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.485-490
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    • 2003
  • In this paper, we propose the possibility of introducing chaotic sequences into digital watermarking systems as potential substitutes to commonly used pseudo noise sequences. Chaotic sequences have several good properties including the availability of a great number of them, the ease of their generation, as well as their sensitive dependence on their initial conditions. And the quantization does not destroy the good property. So this paper proposes a method that transforms Hangul text to chaotic sequence. And we presents how the Hangul text is expressed by an implied data and the implied data is regenerated into the original text. In this paper, we use this implied Hangul text for watermarking.

Application of Geophysical Prospecting to Site Assessment of Waste Landfill (매립지 오염평가를 위한 물리탐사의 적용사례)

  • Lee, Cheol-Hyo;Park, Sam-Gyu
    • 한국지구물리탐사학회:학술대회논문집
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    • 2001.09a
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    • pp.104-121
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    • 2001
  • Recently, the pollution of soil and groundwater becomes a serious social problem, and geophysical exploration methods have been introduced as a remedial investigation method of subsurface. Digital technologies such as personal computer have revolutionized our ability to acquire large volume of data in a short term, and to produce more reliable results for subsurface image. Also, color graphics easily visualizes the survey results in a more understandable manner, and it is widely used for not only characterizing the contaminated subsurface but also monitoring contaminant and remedial process. In this paper, electrical resistivity and electromagnetic (EM) surveys were carried out in order to understand characteristics of waste landfills, and the applicability of geophysical prospecting to site assessment of waste landfill was also tested. According to the result, electrical resistivity and electromagnetic (EM) surveys were effective in estimating distribution of the leachate plume.

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Application of Terrestrial LiDAR for Reconstructing 3D Images of Fault Trench Sites and Web-based Visualization Platform for Large Point Clouds (지상 라이다를 활용한 트렌치 단층 단면 3차원 영상 생성과 웹 기반 대용량 점군 자료 가시화 플랫폼 활용 사례)

  • Lee, Byung Woo;Kim, Seung-Sep
    • Economic and Environmental Geology
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    • v.54 no.2
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    • pp.177-186
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    • 2021
  • For disaster management and mitigation of earthquakes in Korea Peninsula, active fault investigation has been conducted for the past 5 years. In particular, investigation of sediment-covered active faults integrates geomorphological analysis on airborne LiDAR data, surface geological survey, and geophysical exploration, and unearths subsurface active faults by trench survey. However, the fault traces revealed by trench surveys are only available for investigation during a limited time and restored to the previous condition. Thus, the geological data describing the fault trench sites remain as the qualitative data in terms of research articles and reports. To extend the limitations due to temporal nature of geological studies, we utilized a terrestrial LiDAR to produce 3D point clouds for the fault trench sites and restored them in a digital space. The terrestrial LiDAR scanning was conducted at two trench sites located near the Yangsan Fault and acquired amplitude and reflectance from the surveyed area as well as color information by combining photogrammetry with the LiDAR system. The scanned data were merged to form the 3D point clouds having the average geometric error of 0.003 m, which exhibited the sufficient accuracy to restore the details of the surveyed trench sites. However, we found more post-processing on the scanned data would be necessary because the amplitudes and reflectances of the point clouds varied depending on the scan positions and the colors of the trench surfaces were captured differently depending on the light exposures available at the time. Such point clouds are pretty large in size and visualized through a limited set of softwares, which limits data sharing among researchers. As an alternative, we suggested Potree, an open-source web-based platform, to visualize the point clouds of the trench sites. In this study, as a result, we identified that terrestrial LiDAR data can be practical to increase reproducibility of geological field studies and easily accessible by researchers and students in Earth Sciences.