• ETRI Journal
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• 제43권3호
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• pp.538-548
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• 2021

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1447-1453
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• 2020

In this paper, we propose a method for no-reference quality assessment of sports videos using 3D shearlet transform and deep residual neural networks. In the proposed method, 3D shearlet transform-based spatiotemporal features are extracted from the overlapped video blocks and applied to logistic regression concatenated with a deep residual neural network based on a conditional video block-wise constraint to learn the spatiotemporal correlation and predict the quality score. Our evaluation reveals that the proposed method predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.250-253
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• 2009

This paper presents NR (No Reference) Quality assessment method for IPTV or mobile IPTV. Because No Reference quality assessment method does not access the original signal so it is suitable for the real-time streaming service. Our proposed method use decoding parameters, such as quantization parameter, motion vector, and packet loss as a major network parameter. To evaluate performance of the proposed algorithm, we carried out subjective test of video quality with the ITU-T P.910 ACR (Absolute Category Rating) method and obtained the mean opinion score (MOS) value for QVGA 180 video sequence coded by H.264/AVC encoder. Experimental results show the proposed quality metric has a high correlation (84%) to subjective quality.

• 방송공학회논문지
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• 제14권2호
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• pp.127-133
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• 2009

영상통신기술의 발달로, 영상화질평가는 많은 연구자들에 의해 새로운 알고리즘이 연구되었고, 성능은 점차 개선되었다. 하지만, 사람의 주관적인 시각시스템은 너무나 다양하고, 복잡하기 때문에 이를 수식화하고, 객관화하는데 많은 어려움이 있다. 영상의 화질을 평가하는 방법은 전체 기준법 (Full-Reference), 감소기준법 (Reduced-Reference) 그리고 무기준법 (No-Reference)으로 나눌 수 있다. 이중 무기준법은 수신 영상외의 다른 정보가 필요 없기 때문에, 다양한 영상 스트리밍서비스에 사용될 수 있다. 본 연구에서는, 영상의 양자화로 인한 범위 왜곡을 고려한 새로운 무기준법 영상 화질 평가 방법을 제안한다. 그리고, 성능을 비교하기 위해서, ITU-T P910 문서에 따른 주관적 화질 평가를 수행하고, 이를 363개의 영상을 통해 새로운 방법과 기존의 방법을 비교하였다. 실험 결과 제안된 방법의 실제 주관적 화질과의 상관도는 다른 기존방법보다 높은 것으로 나타났다.

• 방송공학회논문지
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• 제14권4호
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• pp.387-396
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• 2009

기존의 무기준 동영상 화질 평가는 디코딩 픽셀 단에서 평가와 전송 에러를 고려한 비트스트림단에서 화질 평가 방법으로 나눌 수 있다. 기존의 방법은 추가 데이터 필요하고 복잡도와 평가 정확도등의 문제가 있어 실제적인 실시간 화질평가에 적용하기에 문제가 많다. 본 연구에서는 실시간 비디오 전송 환경에서 이용될 수 있는 간단하면서도 정확도가 높은 무기준법 화질 평가 방법을 제안한다. 본 논문에서 제안된 무기준법 화질평가 방법은 양자화 파라미터, 전송에러정보, 움직임 벡터정보를 이용한다. 제안된 방법을 검증하기 위해서, ITU-T P.910 ACR(Absolute Category Rating)을 사용하여, 기존의 전체 기준법과 주관적 화질 평가 대비의 상관도를 비교하였는데 제안방법이 85%이상의 상관도를 보여 주었다.

• Journal of Multimedia Information System
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• 제9권2호
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• pp.75-86
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• 2022

The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

• IEIE Transactions on Smart Processing and Computing
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• 제2권5호
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• pp.255-265
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• 2013

3DTV is expected to be a promising next-generation broadcasting service. On the other hand, the visual discomfort/fatigue problems caused by viewing 3D videos have become an important issue. This paper proposes a perceptual quality assessment metric for a stereoscopic video (SV-PQAM). To model the SV-PQAM, this paper presents the following features: temporal variance, disparity variation in intra-frames, disparity variation in inter-frames and disparity distribution of frame boundary areas, which affect the human perception of depth and visual discomfort for stereoscopic views. The four features were combined into the SV-PQAM, which then becomes a no-reference stereoscopic video quality perception model, as an objective quality assessment metric. The proposed SV-PQAM does not require a depth map but instead uses the disparity information by a simple estimation. The model parameters were estimated based on linear regression from the mean score opinion values obtained from the subjective perception quality assessments. The experimental results showed that the proposed SV-PQAM exhibits high consistency with subjective perception quality assessment results in terms of the Pearson correlation coefficient value of 0.808, and the prediction performance exhibited good consistency with a zero outlier ratio value.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.316-320
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• 2009

In this paper, a reference-free perceptual quality metric is proposed for image assessment. It measures the amount of overall blockiness and blurring in the image. And edge-oriented artifacts, such as ringing, mosaic and staircase noise are also considered. In order to give a single quality score, the individual artifact scores are adaptively combined according to the difference between the edge-oriented artifacts and other artifacts. The quality score obtained by the proposed algorithm shows strong correlation with the MOS values by VQEG.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권3호
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• pp.592-606
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• 2011

Currently, the development of multimedia communication has progressed so rapidly that the video program service has become a requirement for ordinary customers. The quality of experience (QoE) for the visual signal is of the fundamental importance for numerous image and video processing applications, where the goal of video quality assessment (VQA) is to automatically measure the quality of the visual signal in agreement with the human judgment of the video quality. Considering the codec effect to the video quality, in this paper an efficient non-reference (NR) VQA algorithm is proposed which estimates the video quality (VQ) only by utilizing the distorted video signal at the destination. The VQA feature vectors (FVs) which have high relationships with the subjective quality of the distorted video are investigated, and a hybrid NR VQA (HNRVQA) function is established by considering the multiple FVs. The simulation results, testing on the SDTV programming provided by VCEG Phase I, show that the proposed algorithm can represent the VQ accurately, and it can be used to replace the subjective VQA to measure the quality of the video signal automatically at the destinations.

• 방송공학회논문지
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• 제13권6호
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• pp.849-858
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• 2008

본 논문에서는 열화된 영상의 화질을 평가함에 있어서 원본 영상을 참조할 필요가 없는 객관적인 평가 방법을 제안한다. 제안하는 알고리듬은 블록 기반의 손실 부호화 과정에서 발생 가능한 블록형 잡음 및 뭉개짐 현상의 정도를 정량화하며, 이와 함께 강한 에지 주변에서 특징적으로 나타나는 물결형 떨림, 계단형 떨림 및 모자이크 잡음 등을 정량화한다. 그리고 퍼지 적분을 이용하여 각각의 잡음의 정도를 통합하여 최종적인 점수를 계산함으로써 주어진 영상의 화질을 평가한다. 제안 알고리듬에 따라 얻어진 화질 평가 결과는 전문가 집단에 의한 주관적 화질 평가 결과와 높은 유사성을 보인다.