• Title/Summary/Keyword: Human visual system

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Modeling for Hue Shift Effect of Human Visual System on High Luminance Display (고휘도 디스플레이에서의 인간 시각에 따른 색상 이동 현상과 모델링)

  • Lee, Tae-Hyoung;Lee, Myong-Young;Park, Kee-Hyon;Ha, Yeong-Ho
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.307-308
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    • 2006
  • In recent, displays have very good properties at high luminance, fast response, and size. Also They have good quality in terms of color according to the development of the gamut extension and color reproduction. However, despite these merits, there is a characteristic that at a high luminance display, observer perceive the different color from the originally re-producted color due to the change of perceived luminance in human visual system. In this paper, we propose a model that is the hue shift phenomenon between a normal display and a high luminance display, and then an algorithm which compensate the color between two devices, so that observer can perceive the same color.

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Image and Display Quality Evaluation

  • Ha, Yeong-Ho
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1224-1227
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    • 2009
  • When evaluating the quality of images and displays, it is important to combine the characteristics as perceived by the human visual system and measured by equipment using subjective and objective methods, respectively. In the case of objective methods, the quality of a display is measured using colorimetric or radiometric devices according to existing standards covering the color temperature, gamut size, gamma characteristic, and device characterization. Meanwhile, subjective methods assess the quality of an image using the human visual system based on a comparison with a reference or counterpart using such metrics as the sharpness, noise, contrast, saturation, and color accuracy. Objective and subjective methods are usually used together in comparison, as ultimately it is observers watching images on a display. In addition to existing objective methods, a new image quality metric is also introduced as regards the JPEG compression ratio that is reflected in the relationship between the gamut size and the color fidelity in CIELAB color space.

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Halftoning Method by CMY Printing Using BNM

  • Kim, Yun-Tae;Kim, Jeong-Yeop;Kim, Hee-Soo;Yeong Ho ha
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.851-854
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    • 2000
  • Digital halftoning is a technique to make an equivalent binary image from scanned photo or graphic images. Low pass filtering characteristic of human visual system can be applied to get the effect of spatial averaging of local area consisted of black and white pixels for gray image. The overlapping of black dot decreases brightness and black dot is very sensitive to human visual system in the bright region. In this paper, for gray-level expression, only bright gray region in the color image is considered for blue noise mask (BNM) approach. To solve this problem, BNM with CMY dot is used for the bright region instead of black dot. Dot-on-dot model with single mask causes the problem making much black dot overlap, color distortion. Therefore approach with three masks for C, M and Y each is proposed to decrease pixel overlap and color distortion.

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An Adaptive Noise Removal Method Using Local Statistics and Generalized Gaussian Filter (국부 통계 특성 및 일반화된 Gaussian 필터를 이용한 적응 노이즈 제거 방식)

  • Song, Won-Seon;Nguyen, Tuan-Anh;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.1C
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    • pp.17-23
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    • 2010
  • In this paper, we present an adaptive noise removal method using local statistics and generalized Gaussian filter. we propose a generalized Gaussian filter for removing noise effectively and detecting noise adaptively using local statistics based human visual system. The simulation results show the objective and subjective capabilities of the proposed algorithm.

Visual Analysis of Deep Q-network

  • Seng, Dewen;Zhang, Jiaming;Shi, Xiaoying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.853-873
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    • 2021
  • In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

A Study on Positive and Negative Visual Stimuli using the Real-Time Human Sensibility Assessment System (실시간 주관적 감성 평가시스템을 이용한 긍정 및 부정 시각자극에 대한 연구)

  • Min, Byeong-Chan;Jeong, Sun-Cheol;Min, Byeong-Un;Sin, Mi-Gyeong;Jeong, Hak-Gi;Kim, Cheol-Jung
    • Journal of the Ergonomics Society of Korea
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    • v.20 no.1
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    • pp.31-43
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    • 2001
  • The present study the feasibility of the new subjective assessment devise; Real-Time Subjective Assessment Digitizer (RTSAD). The subjects were instructed to evaluate their sensibility during the presentation of the positive and the negative visual stimuli using RTSAD. After the presentation of each of the stimulus, a questionnaire was used for comparing the results with those from RTSAD. It was argued that the biggest utility of the RTSAD is the capability of measuring and figuring out the trends of the subjective assessment in real time. The results from the questionnaires unlike the results from RTSAD, reflects only the averaged human sensibility for the entire time of the presentation of the stimulus.

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Human Vision System based Adaptive Watermarking Algorithm (시각적 특성에 기반한 적응적 워터마킹 알고리즘)

  • 전영민;고일주;김계영
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.6
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    • pp.101-109
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    • 2004
  • This paper proposes an adaptive watermarking algerian technique concerning the visual characteristics of human. To embed watermark to an image, features such as contrast, brightness, and texture are used. The propose method adaptively select blocks and determine the position and intensity of watermark to be applied, concerning the visual characteristics of a human. The experiment involves cropping, image enhancement, low pass filtering, and JPEG compression, which are compared on detectability of watermark against image manipulation and attack

The Binary Tree Vector Quantization Using Human Visual Properties (인간의 시각 특성을 이용한 이진 트리 벡터 양자화)

  • 유성필;곽내정;박원배;안재형
    • Journal of Korea Multimedia Society
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    • v.6 no.3
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    • pp.429-435
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    • 2003
  • In this paper, we propose improved binary tree vector quantization with consideration of spatial sensitivity which is one of the human visual properties. We combine weights in consideration with the responsibility of human visual system according to changes of three primary color in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. Also we propose the novel quality measure of the quantization images that applies MTF(modulation transfer function) to luminance value of quantization error of color image. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get less quantized level images and can reduce the resource occupied by the quantized image.

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A Study on Detecting Optimal Corner Points using Morphology and Human Visual Concept (수리 형태학과 인간의 시각적 개념을 이용한 최적의 코너 점 추출을 위한 연구)

  • Jeong, Gi-Ryong
    • Journal of Navigation and Port Research
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    • v.28 no.3
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    • pp.233-238
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    • 2004
  • Comer point is a very important information to a pattern recognition of image processing. And so, many researchers develope various detecting comer point algoritms. But, there are some problems to get comer points by 8 directional chain code when the degree of edge line is not integer multiplication of 45 degree. So, we propose a new algorithm which is combined with morphology and human visual conception for optimal comer points without the above defects. We get a good simulation result by this proposed algorithm Ana so, we think this algorithm is very useful to FA(factory automation} and ship's radar system to know some coastal area from its image.

Structural Similarity Based Video Quality Metric using Human Visual System (구조적 유사도 기반의 인간의 시각적 특성을 이용한 비디오 품질 측정 기준)

  • Park, Jin-Cheol;Lee, Sang-Hoon
    • Journal of Broadcast Engineering
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    • v.14 no.1
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    • pp.36-43
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    • 2009
  • Recently, the structural similarity (SSIM) index metric is proposed. In the present paper, a new framework, which is called visual SSIM (VSSIM), is proposed by incorporating crucial human factors into the SSIM. The human factors are foveation, luminance, frequency and motion information. The performance of VSSIM is evaluated by subjective quality test compliant with the Video Quality Expert Group (VQEG) multimedia group test plan. It shows that the visual SSIM is more correlated with the subjective quality result than the conventional SSIM.