• Title/Summary/Keyword: Peak Signal-to-Noise Ratio (PSNR)

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Camouflage Pattern Evaluation based on Environment and Camouflage Pattern Similarity Analysis (작전환경 및 위장무늬 유사도 분석 기반 위장무늬 평가)

  • Yun, Jeongrok;Kim, Hoemin;Kim, Un Yong;Chun, Sungkuk
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.671-672
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    • 2021
  • 본 논문에서는 작전환경과 위장무늬 디자인 영상 간의 색상 및 구조 분석 기반의 새로운 정량적 위장무늬 평가 방법을 제안한다. 작전환경 및 위장무늬 디자인 영상 간 RGB, Lab 색상 공간에서의 화소간 평균 오차 및 색상 히스토그램 비교를 통해 색상 유사도를 계산한다. 또한, PSNR(Peak Signal-to-Noise Ratio), MSSIM(Mean Structural Similarity Index), UIQI, GMSD 및 딥러닝 기반 영상 간 구조 유사도를 계산한다. Random Forest Regressor를 통해 각각 계산된 색상 및 구조 유사도 파라미터를 회기 분석하여 최종 위장무늬 평가 결과를 계산한다. 20명의 피실험자를 대상으로 제안한 위장무늬 평가 방법과 기존 평가 방법을 비교함을 통해 제안한 방법의 성능을 검증하였다.

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Convergence Performance Evaluation of Radiation Protection for Apron using the PSNR (최대 신호 대 잡음비를 이용한 방사선 방어용 앞치마의 융복합 성능평가)

  • Kim, Dae-Ho;Kim, Sang-Hyun
    • Journal of Digital Convergence
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    • v.13 no.10
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    • pp.377-383
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    • 2015
  • This study evaluates the convergence radiation protection performance by measuring the PSNR(peak signal-to-noise ratio) values of the image J in the image evaluation program based on increased relative to this exposure of radiation workers.The aim of this study was to evaluate radiation protection performance of apron for design of it's basic information. Method was used to PSNR of Image J program and good condition apron was more than 27dB, the PSNR value of poor condition apron appeared to be less than 24dB. The result is the normality were satisfied distribution and T-test values were statistically significant with p<0.001. Results of evaluation of the performance protective apron through the more easily accessible experimental conditions and methods in the clinical was confirmed distinctly different. in order to reduce the radiation exposure we need to evaluate convergence protection performance and to be having a good performance apron.

A Fast Block Matching Algorithm using Unit-Diamond and Flat-Hexagonal Search Patterns (단위 다이아몬드와 납작한 육각패턴을 이용한 고속 블록 정합 알고리즘)

  • 남현우;위영철;김하진
    • Journal of KIISE:Computing Practices and Letters
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    • v.10 no.1
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    • pp.57-65
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    • 2004
  • In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the unit-diamond search pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the unit-diamond search pattern, and then fastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed unit-diamond and flat-hexagonal pattern search algorithm(UDFHS) improves as high as 11∼51% in terms of average number of search point per motion vector estimation and improves about 0.05∼0.74㏈ in terms of PSNR(Peak Signal to Noise Ratio).

Hybrid Down-Sampling Method of Depth Map Based on Moving Objects (움직임 객체 기반의 하이브리드 깊이 맵 다운샘플링 기법)

  • Kim, Tae-Woo;Kim, Jung Hun;Park, Myung Woo;Shin, Jitae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37A no.11
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    • pp.918-926
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    • 2012
  • In 3D video transmission, a depth map being used for depth image based rendering (DIBR) is generally compressed by reducing resolution for coding efficiency. Errors in resolution reduction are recovered by an appropriate up-sampling method after decoding. However, most previous works only focus on up-sampling techniques to reduce errors. In this paper, we propose a novel down-sampling technique of depth map that applies different down-sampling rates on moving objects and background in order to enhance human perceptual quality. Experimental results demonstrate that the proposed scheme provides both higher visual quality and peak signal-to-noise ratio (PSNR). Also, our method is compatible with other up-sampling techniques.

A Block Matching Algorithm using Motion Vector Predictor Candidates and Adaptive Search Pattern (움직임 벡터 예측 후보들과 적응적인 탐색 패턴을 이용하는 블록 정합 알고리즘)

  • Kwak, Sung-Keun;Wee, Young-Cheul;Kim, Ha-JIne
    • The KIPS Transactions:PartB
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    • v.11B no.3
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    • pp.247-256
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    • 2004
  • In this paper, we propose the prediction search algorithm for block matching using the temporal/spatial correlation of the video sequence and the renter-biased property of motion vectors The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate pint in each search region and the predicted motion vector from the neighbour blocks of the current frame. And the searching process after moving the starting point is processed a adaptive search pattern according to the magnitude of motion vector Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 0.75dB as depend on the video sequences and improved about 0.05∼0.34dB on an average except the FS (Full Search) algorithm.

Adaptive De-interlacing Algorithm using Method Selection based on Degree of Local Complexity (지역 복잡도 기반 방법 선택을 이용한 적응적 디인터레이싱 알고리듬)

  • Hong, Sung-Min;Park, Sang-Jun;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.4C
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    • pp.217-225
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    • 2011
  • In this paper, we propose an adaptive de-interlacing algorithm that is based on the degree of local complexity. The conventional intra field de-interlacing algorithms show the different performance according to the ways which find the edge direction. Furthermore, FDD (Fine Directional De-interlacing) algorithm has the better performance than other algorithms but the computational complexity of FDD algorithm is too high. In order to alleviate these problems, the proposed algorithm selects the most efficient de-interacing algorithm among LA (Line Average), MELA (Modified Edge-based Line Average), and LCID (Low-Complexity Interpolation Method for De-interlacing) algorithms which have low complexity and good performance. The proposed algorithm is trained by the DoLC (Degree of Local Complexity) for selection of the algorithms mentioned above. Simulation results show that the proposed algorithm not only has the low complexity but also performs better objective and subjective image quality performances compared with the conventional intra-field methods.

Toward 6 Degree-of-Freedom Video Coding Technique and Performance Analysis (6 자유도 전방위 몰입형 비디오의 압축 코덱 개발 및 성능 분석)

  • Park, Hyeonsu;Park, Sang-hyo;Kang, Je-Won
    • Journal of Broadcast Engineering
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    • v.24 no.6
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    • pp.1035-1052
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    • 2019
  • Recently, as the demand for immersive videos increases, efficient video processing techniques for omnidirectional immersive video is actively developed by MPEG-I. While the omnidirectional video provides a larger degree of freedom for a free viewpoint, the size of the video increases significantly. Furthermore, in order to compress 6 degree-of-freedom (6 DoF) videos that support motion parallax, it is required to develop a codec to yield better coding efficiency. In this paper, we develop a 6 DoF codec using Versatile Video Coding (VVC) as the next generation video coding standard. To the authors' best knowledge, this is the first VVC-based 6 DoF video codec toward the future ISO/IEC 23090 Part 7 (Metadata for Immersive Media (Video)) MPEG-I standardization. The experiments were conducted on the seven test video sequences specified in Common Test Condition (CTC) in two operation modes of TMIV (Test Model for Immersive Media) software. It is demonstrated that the proposed codec improves coding performance around 33.8% BD-rate reduction in the MIV (Metadata for Immersive Video) mode and 30.2% BD-rate reduction in the MIV view mode as compared to the state-of-the-art TMIV reference software. We also show the performance comparisons using Immersive Video PSNR (IV-PSNR) and Mean Structural Similarity (MSSIM).

A Prediction Search Algorithm in Video Coding by using Neighboring-Block Motion Vectors (비디오 코딩을 위한 인접블록 움직임 벡터를 이용한 예측 탐색 알고리즘)

  • Kwak, Sung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.8
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    • pp.3697-3705
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    • 2011
  • There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose a new prediction search algorithm for block matching using the temporal and spatial correlation of the video sequence and local statistics of neighboring motion vectors. The proposed ANBA(Adaptive Neighboring-Block Search Algorithm) determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and use a previous motion vector. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06dB as depend on the video sequences and improved about 0.01~0.64dB over MVFAST and PMVFAST.

An effective quality improvement scheme of magnified image using the surface characteristics in image (영상의 곡면 특성을 활용한 효과적인 확대영상의 화질 향상 기법)

  • Jung, Soo-Mok;On, Byung-Won
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.8
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    • pp.45-54
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    • 2014
  • In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

A Fast Block Matching Motion Estimation Algorithm by using an Enhanced Cross-Flat Hexagon Search Pattern (개선된 크로스-납작한 육각 탐색 패턴을 이용한 고속 블록 정합 움직임 예측 알고리즘)

  • Nam, Hyeon-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.7
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    • pp.99-108
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    • 2008
  • For video compression, we have to consider two performance factors that are the search speed and coded video's quality. In this paper, we propose an enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased characteristic of motion vectors(MV). The proposed algorithm first finds a predicted motion vector from the adjacent macro blocks of the current frame and determines an exact motion vector using the cross pattern and a flat hexagon search pattern. From the performance evaluations, we can see that our algorithm outperforms both the hexagon-based search(HEXBS) and the cross-hexagon search(CHS) algorithms in terms of the search speed and coded video's quality. Using our algorithm, we can improve the search speed by up to 31%, and also increase the PSNR(Peak Signal Noise Ratio) by at most 0.5 dB, thereby improving the video quality.

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