• 제목/요약/키워드: Statistical Image Quality Measure

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통계적 영상 품질 측정 (Statistical Image Quality Measure)

  • 배경율
    • 지능정보연구
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    • 제13권4호
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    • pp.79-90
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    • 2007
  • 영상의 품질을 측정하는 것은 영상처리에서 매우 중요한 문제이다. 지금까지 영상 품질을 측정하기 위한 다양한 방법들이 제시되었고, 이들은 수학적인 관점에서 영상의 품질을 적절히 표현해주고 있다. 그러나, 수학적인 측정과 인간의 시각에 의해서 측정되는 품질은 서로 다를 수 있고 영상이 전달되는 최종 대상체는 인간의 시각이기 때문에 이를 고려한 영상품질 측정 방법이 필요하다. 본 논문에서는 사람의 시각적 특성을 고려하여 영상 품질을 측정할 수 있는 통계적 방법을 제시하였다. 사람의 시각은 영상의 전체적인 품질을 판단하면서도 국부적인 위치에서의 품질을 판단하며, 전체적인 영상의 품질보다는 국부적인 위치에서의 품질이 시각적인 영상품질 판단에 미치는 영향이 크다. 본 논문에서는 영상을 세그먼트화하고 각 세그먼트화된 영상에서 얻어진 영상 품질 값에 스코어링을 하는 통계적 기법을 사용하여 시각에 의한 판단과 유사한 결과를 얻었다.

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Digital Image Quality Assessment Based on Standard Normal Deviation

  • Park, Hyung-Ju;Har, Dong-Hwan
    • International Journal of Contents
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    • 제11권2호
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    • pp.20-30
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    • 2015
  • We propose a new method that specifies objective image quality factors by evaluating an image quality measurement model using random images. In other words, No-Reference variables are used to evaluate the quality of an original image without using any reference for comparison. 1000 portrait images were collected from a web gallery with votes constituting over 30 recommendation values. The bottom-up data collecting process was used to calculate the following image quality factors: total range, average, standard deviation, normalized distribution, z-score, preference percentage. A final grade is awarded out of 100 points, and this method ranks and grades the final estimated image quality preference in terms of total image quality factors. The results of the proposed image quality evaluation model consist of the specific dynamic range, skin tone R, G, B, L, A, B, and RSC contrast. We can present the total for the expected preference points as the average of the objective image qualities. Our proposed image quality evaluation model can measure the preferences for an actual image using a statistical analysis. The results indicate that this is a practical image quality measurement model that can extract a subject's preferred image quality.

국내 G3 팩시밀리 화상품질에 관한 통계 분석 (Statistical Analysis on the Measurement of the Image Quality of G3 facsimile)

  • 이성덕;권세혁
    • 품질경영학회지
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    • 제23권2호
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    • pp.1-9
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    • 1995
  • Two user groups, expert and non-expert, are sampled to measure the image quality of G3 facsimile. A ITU-TS tset chart No. 2 has been transmitted among some selected cities and evaluated by user groups. Their subjective evaluation to the image quality is quantified by Mean Opinion Score method. There is highly significant difference in the image quality between expert and non-expert. From modified logit model, it is concluded that there is no significance in two considered factors, the effects of the number of links and transmission time. The derived percent curves show that 80% of non-experts(90% of expert) is considering the image quality of G3 facsimile "fair, good, or excellent".

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쉬어렛 변환의 복소수 특성을 이용하는 무참조 영상 화질 평가 (No-Reference Image Quality Assessment Using Complex Characteristics of Shearlet Transform)

  • 사이드 마흐모드포어;김만배
    • 방송공학회논문지
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    • 제21권3호
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    • pp.380-390
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    • 2016
  • 화질 평가 방법은 그동안 많은 방법이 소개되어 왔다. 특히 우수한 성능을 보여주는 무참조 평가에서 기법에서 발전이 지속되어 왔다. 본 논문에서는 쉬어렛 영역에서 자연영상의 통계적 특성에 기반한 무참조 영상화질 평가 방법을 제안한다. 제안 방법은 쉬어릿 계수의 통계 특성으로부터 왜곡에 민감한 특징을 추출한다. 쉬어렛 변환의 복소수 계수로부터 위상과 크기 특징을 얻어낸다. 또한 쉬어렛 변환은 다양한 스케일로 영상을 분석할 수 있기 때문에, 스케일간의 계수의 의존성에 대한 왜곡의 영향을 분석한다. 화질 예측을 위해서 특징들은 SVM(support vector machine)을 이용하여 영상 왜곡 분류 및 화질 예측에 활용된다. 실험결과는 제안 방법이 주관적 평가와의 높은 상관도를 보여주고, 또한 기존 참조 및 무참조 방법보다 우수한 성능을 보여준다.

Adaptive Noise Reduction Algorithm for an Image Based on a Bayesian Method

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.619-628
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    • 2012
  • Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise; however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.

가우시안 프로세스 회귀분석을 이용한 영상초점으로부터의 3차원 형상 재구성 (3D Shape Recovery from Image Focus using Gaussian Process Regression)

  • 무하마드 타릭 마흐무드;최영규
    • 반도체디스플레이기술학회지
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    • 제11권3호
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    • pp.19-25
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    • 2012
  • The accuracy of Shape From Focus (SFF) technique depends on the quality of the focus measurements which are computed through a focus measure operator. In this paper, we introduce a new approach to estimate 3D shape of an object based on Gaussian process regression. First, initial depth is estimated by applying a conventional focus measure on image sequence and maximizing it in the optical direction. In second step, input feature vectors consisting of eginvalues are computed from 3D neighborhood around the initial depth. Finally, by utilizing these features, a latent function is developed through Gaussian process regression to estimate accurate depth. The proposed approach takes advantages of the multivariate statistical features and covariance function. The proposed method is tested by using image sequences of various objects. Experimental results demonstrate the efficacy of the proposed scheme.

확률적 방법을 통한 컬러 영상 분할 (Color Image Segmentation by statistical approach)

  • 강선도;유헌우;장동식
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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    • pp.1677-1683
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    • 2006
  • Color image segmentation is useful for fast retrieval in large image database. For that purpose, new image segmentation technique based on the probability of pixel distribution in the image is proposed. Color image is first divided into R, G, and B channel images. Then, pixel distribution from each of channel image is extracted to select to which it is similar among the well known probabilistic distribution function-Weibull, Exponential, Beta, Gamma, Normal, and Uniform. We use sum of least square error to measure of the quality how well an image is fitted to distribution. That P.d.f has minimum score in relation to sum of square error is chosen. Next, each image is quantized into 4 gray levels by applying thresholds to the c.d.f of the selected distribution of each channel. Finally, three quantized images are combined into one color image to obtain final segmentation result. To show the validity of the proposed method, experiments on some images are performed.

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Correlation analysis between radiation exposure and the image quality of cone-beam computed tomography in the dental clinical environment

  • Song, Chang-Ho;Yeom, Han-Gyeol;Kim, Jo-Eun;Huh, Kyung-Hoe;Yi, Won-Jin;Heo, Min-Suk;Lee, Sam-Sun
    • Imaging Science in Dentistry
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    • 제52권3호
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    • pp.283-288
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    • 2022
  • Purpose: This study was conducted to measure the radiation exposure and image quality of various cone-beam computed tomography (CBCT) machines under common clinical conditions and to analyze the correlation between them. Materials and Methods: Seven CBCT machines used frequently in clinical practice were selected. Because each machine has various sizes of fields of view (FOVs), 1 large FOV and 1 small FOV were selected for each machine. Radiation exposure was measured using a dose-area product (DAP) meter. The quality of the CBCT images was analyzed using 8 image quality parameters obtained using a dental volume tomography phantom. For statistical analysis, regression analysis using a generalized linear model was used. Results: Polymethyl-methacrylate (PMMA) noise and modulation transfer function (MTF) 10% showed statistically significant correlations with DAP values, presenting positive and negative correlations, respectively (P<0.05). Image quality parameters other than PMMA noise and MTF 10% did not demonstrate statistically significant correlations with DAP values. Conclusion: As radiation exposure and image quality are not proportionally related in clinically used equipment, it is necessary to evaluate and monitor radiation exposure and image quality separately.

해양의료관광지의 방문의도에 관한 탐색적 연구 (An Exploratory Study on Visit Intention of Destination in Marine Health Tourism)

  • 김민철;부창산
    • 수산해양교육연구
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    • 제27권1호
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    • pp.230-242
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    • 2015
  • The purpose of this study is to propose, firstly, the definition of marine health tourism and empirically to analyse the effect of benefit sought and brand equity on visit intention of destination as marine health tourism. This study utilizes the PLS-SEM method in order to measure the overall model fitness level and statistical significance of all paths in proposed research model. As a result of the analysis, benefit sought factor like nature has a highest positive effect on brand equity(image and perceived quality) and also, on visit intention via brand equity. Specially, this study measures the non-linear of all the paths and shows the statistical significance that the more high health factor as benefit sought is, the preference for quality brands is more steeply. In addition, the measurement of the moderating effect of gender variables shows that female is the most sensitive than male on the path from health benefit sought to brand quality among all the paths. However, the definition of marine health tourism in this study is proposed according to the characteristics of a particular area. In this vein, the definition is needed to generalize more through follow-up study.

Object Tracking using Adaptive Template Matching

  • Chantara, Wisarut;Mun, Ji-Hun;Shin, Dong-Won;Ho, Yo-Sung
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권1호
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    • pp.1-9
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    • 2015
  • Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.