• 전자공학회논문지
• /
• 제50권4호
• /
• pp.127-136
• /
• 2013

본 논문은 동영상 프레임 간 선명도를 균일하게 유지하면서 블러를 제거하는 기법을 제안한다. 고정된 변수들을 이용하는 기존 기법들과 달리, 제안하는 동영상 디블러링 기법은 영상에 따라 디블러 변수들을 조절함으로써 선명도를 균일하게 만들어 준다. 먼저, 입력 프레임의 초기 블러 커널을 추정하고, 디컨볼루션을 수행한 뒤, 선명도를 측정한다. 그리고 균일한 선명도를 유지할 수 있도록 측정된 선명도에 기반하여 정규화 변수와 커널을 조절하고, 다시 디컨볼루션을 수행한다. 실험 결과를 통해 제안 기법이 상당히 균일한 선명도를 유지하면서 디블러링을 수행함을 확인할 수 있다.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2007년도 춘계학술대회논문집
• /
• pp.137-140
• /
• 2007

A prediction model for the sound quality of household refrigerator noise was proposed by investigating subjective and objective attributes of the noise [Jeon et al. (2007) Appl. Acoust.]. In the present study, the just noticeable difference (JND) of each sound quality metric - Zwicker's loudness, sharpness, roughness and fluctuation strength - which constitute the prediction model was investigated. Loudness of recorded sound samples from five refrigerators were varied according to constant intervals in sound pressure levels. Sharpness was also changed at 14-16 barks. Auditory experiments were conducted to discriminate the JNDs of loudness and sharpness by method of limit. The results indicated that JNDs of loudness and sharpness were 0.50 sone and 0.08 acum, respectively.

• 방송공학회논문지
• /
• 제17권3호
• /
• pp.459-470
• /
• 2012

본 논문은 영상 보간법을 이용하여 저해상도 깊이맵을 고해상도 깊이맵으로 변환하는 방법을 제안한다. 현재의 카메라 센서는 고해상도 색상 영상을 제공하는데 반해, 깊이 측정 장치는 저해상도의 깊이맵을 주로 제공한다. 본 논문은 기존의 양선형 보간법, 고등차수 보간법, 양측 보간법을 바탕으로 깊이맵에서 추출한 고주파 성분을 적용하여 깊이맵의 선명도를 증가한다. 이를 위해, 제안 방법은 고주파 성분 추출 단계, 고주파 성분 적용 단계, 및 영상 보간 단계를 거친다. 실험에서는 다양한 깊이맵 데이터에 제안 방법을 적용하였는데, 성능검증 방법으로 선명도(sharpness degree)와 블러 메트릭 (blur metric)의 두 객관적 측정을 통해서 제안 방법이 기존 방법에 비해 선명도가 약 2배 정도 증가했음을 보여준다. 또한 블러 메트릭은 평균 14%가 감소되었다.

• 반도체디스플레이기술학회지
• /
• 제19권3호
• /
• pp.7-11
• /
• 2020

Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about the blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operators is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on the local binary pattern (LBP) with the adaptive threshold for blur detection. The sharpness metric developed based on LBP uses a fixed threshold irrespective of the blur type and level which may not be suitable for images with large variations in imaging conditions and blur type and level. Contradictory, the proposed measure uses an adaptive threshold for each image based on the image and the blur properties to generate an improved sharpness metric. The adaptive threshold is computed based on the model learned through the support vector machine (SVM). The performance of the proposed method is evaluated using a well-known dataset and compared with five state-of-the-art methods. The comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all the methods.

• 방송공학회논문지
• /
• 제19권1호
• /
• pp.31-43
• /
• 2014

깊이맵은 3D 입체영상의 생성을 위해 중요한 요소이다. 하지만 깊이 카메라를 이용하여 획득한 깊이맵들은 낮은 해상도를 갖는 단점이 있기 때문에 이를 고해상도로 변환하는 연구들이 활발하게 진행되고 있다. 이러한 연구들은 일반적으로 PSNR, Sharpness Degree, Blur Metric 등과 같은 객관적인 평가방법으로 성능을 검증해왔다. 이러한 평가방법 이외에 DIBR로 가상시점(virtual view)을 생성하여 주관적으로 평가하는 연구도 있으나, 입체영상을 생성하여 깊이맵 업샘플링의 성능을 분석하는 것은 많지 않다. 본 논문에서는 다양한 깊이맵 업샘플링 방법들을 이용하여 생성된 입체영상의 주관적 평가와 업샘플링 방법의 객관적 평가 결과의 상관관계 및 선형회귀법을 이용하여 관련성을 분석한다. 실험결과에서는 에지 PSNR이 시각적 피로도와의 상관관계가 가장 높고, Blur Metric은 가장 낮다는 것을 보여준다. 또한 선형회귀에서는 최적의 입체영상을 얻을 수 있는 객관적 평가의 가중치를 구하고, 기존 또는 새로운 업샘플링 알고리즘의 3D성능을 예측할 수 있는 공식을 보여준다.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2014년도 추계학술대회 논문집
• /
• pp.785-790
• /
• 2014

The purpose of this study is to identify the significant sound quality metric and compose the sound quality index of motor driven roller blind which is part of vehicle sunroof. Before subjective evaluation, sound characteristics of roller blind was analyzed and set the target operating sound for subjective evaluation. Thus, transfer sound of roller blind which has the characteristics of sound modulation was used for subjective evaluation. Linear regression was carried out by chosen Zwicker's metrics which are pointed by comments of jurors. Loudness and sharpness related metrics are prime metrics in sound quality index we composed. Effect of roller blind assay when it is attached to real vehicle was identified to evaluate the validity of index.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
• /
• pp.1224-1227
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권2호
• /
• pp.907-923
• /
• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• 한국소음진동공학회논문집
• /
• 제25권5호
• /
• pp.345-351
• /
• 2015

Sounds of electrically powered vehicle components such as window lift system, roller blind, etc., are required to be more comfortable and not to irritate the people emotionally. In this paper, a study was conducted to identify the significant sound quality metric and compose the luxuriousness sound quality index of electrically powered vehicle roller blind which is part of vehicle sunroof system. Before conducting subjective evaluation, sound characteristics of roller blind was analyzed and set the target operating sound for subjective evaluation. Thus, transfer sound of roller blind which has the characteristics of sound modulation was used for subjective evaluation. Multiple linear regression analysis was carried out by chosen Zwicker's metrics which are pointed by comments of jurors. Loudness and sharpness related metrics are prime metrics in luxuriousness sound quality index we composed. Also, effect of roller blind assay when it is attached to real vehicle was identified to evaluate the validity of index.

• 한국소음진동공학회논문집
• /
• 제15권7호
• /
• pp.821-828
• /
• 2005

In our life, we have used many digital appliances. They help us to improve the quality of life but sometimes give us unsatisfactory result. Because they produce specific noise. Especially vacuum cleaner produce much noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we develop sound quality index for vacuum cleaner using the sound quality metrics defined in psychoacoustics. First, we carry out the subjective evaluation of vacuum cleaner sound to verify what vacuum sound feels good to human. And then artificial neural network estimated the complexity and the nonlinear characteristics of the relations between subjective evaluation and sound metrics. Finally the ANN is trained repeatedly to have a good performance for sound qualify index of the vacuum cleaner. As a result, the sound quality index of vacuum cleaner has a correlation of $93.5\%$ between the subjective evaluation and ANN. So, there exist three factors that Is loudness, sharpness, roughness which affect the sound quality of vacuum cleaner.