• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.655-661
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• 2011

The transmission issues for the scalable video coding extension of H.264/AVC (H.264 SVC) video has been widely studied. In this paper, we propose an objective video-quality assessment metric based on no-reference for H.264 SVC using scalability information. The proposed metric estimate the perceptual video-quality reflecting error conditions with the consideration of the motion vectors, error propagation patterns with the hierarchical prediction structure, quantization parameters, and number of frame which damaged by packet loss. The proposed metric reflects the human perceptual quality of video and we evaluate the performance of proposed metric by using correlation relationship between differential mean opinion score (DMOS) as a subjective quality and proposed one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1388-1399
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• 2012

This paper proposes a quality metric based on a No-Reference Bitstream (NR-B) having least computational complexity for the assessment of the human-perceptual quality of H.264 encoded video. The proposed NR-B method performs a modeling of encoding distortion with three bit-stream information (i.e. frame-rate, motion-vector, and quantization-parameter) that can be directly extractable from the encoded bitstream and does not require additional complex processing of final pictures. From performance evaluation using 165 compressed video sequences, the experiment results show that the proposed metric has a higher correlation with subjective quality than is achieved with other comparable methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2529-2543
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• 2019

Scanning electron microscopy (SEM) image can link with the microscopic world through reflecting interaction between electrons and materials. The SEM images are easily subject to blurring distortions during the imaging process. Inspired by the fact that dark channel prior captures the changes to blurred SEM images caused by the blur process, we propose a method to evaluate the SEM images sharpness based on the dark channel prior. A SEM image database is first established with mean opinion score collected as ground truth. For the quality assessment of the SEM image, the dark channel map is generated. Since blurring is typically characterized by the spread of edge, edge of dark channel map is extracted. Then noise is removed by an edge-preserving filter. Finally, the maximum gradient and the average gradient of image are combined to generate the final sharpness score. The experimental results on the SEM blurred image database show that the proposed algorithm outperforms both the existing state-of-the-art image sharpness metrics and the general-purpose no-reference quality metrics.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.380-390
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• 2016

The field of Image Quality Measure (IQM) is growing rapidly in recent years. In particular, there was a significant progress in No-Reference (NR) IQM methods. In this paper, a general-purpose NR IQM algorithm is proposed based on the statistical characteristics of natural images in shearlet domain. The method utilizes a set of distortion-sensitive features extracted from statistical properties of shearlet coefficients. A complex version of the shearlet transform is employed to take advantage of phase and amplitude features in quality estimation. Furthermore, since shearlet transform can analyze the images at multiple scales, the effect of distortion on across-scale dependencies of shearlet coefficients is explored for feature extraction. For quality prediction, the features are used to train image classification and quality prediction models using a Support Vector Machine (SVM). The experimental results show that the proposed NR IQM is highly correlated with human subjective assessment and outperforms several Full-Reference (FR) and state-of-art NR IQMs.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.552-560
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• 2011

In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.96-104
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• 2009

In this paper, we propose a no-reference objective Quality assessment metrics of image. The blockiness and blurring of edge areas which are sensitive to the human visual system are modeled as step functions. Blocking and blur metrics are obtained by estimating local visibility of blockiness and edge width, For the blocking metric, horizontal and vertical blocking lines are first determined by accumulating weighted differences of adjacent pixels and then the local visibility of blockiness at the intersection of blocking lines is obtained from the total difference of amplitudes of the 2-D step function which is modelled as a blocking region. The blurred input image is first re-blurred by a Gaussian blur kernel and an edge mask image is generated. In edge blocks, the local edge width is calculated from four directional projections (horizontal, vertical and two diagonal directions) using local extrema positions. In addition, the kurtosis and SSIM are used to compute the blur metric. The final no-reference objective metric is computed after those values are combined using an appropriate function. Experimental results show that the proposed objective metrics are highly correlated to the subjective data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.410-413
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• 2011

2012년 12월 31일을 기점으로 지상파 아날로그 방송이 종료되고 디지털 방송으로 전환되게 되어, 아날로그 방송에서는 크게 느껴지지 못했던, HDTV 영상 화질에 대한 문제가 대두되고 있다. 방송에서 쓰이는 영상의 경우 대부분 원본은 Tape형식이고, 이를 디지털방송에 맞는 형식으로 압축하여 인코딩한 이후 방송에 적합한 형태로 가공하여 서비스하게 되는데, 이때 MPEG압축 방식에 의해 발생하는 블로킹과 같은 새로운 증상에 대한 문제점이 나타나게 된다. 본 논문에서는, HDTV 영상 화질에서의 일반적으로 인간의 시각이 민감하게 반응하는 블록형 잡음에 대하여, 원본비참조 방법으로, 블록들에 대한 객관적인 점수화 방법에 대하여 연구한다. 본 연구를 통해 HDTV의 고품질화와 정보통신 영상 발전에 기여 할 것이다.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.631-648
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• 2012

The integrative ecological approaches of chemical assessments, physical habitat modelling, and multi-metric biological health modelling were applied to Gwanpyeong Stream within Gap-Stream watersheds to evaluate environmental impacts on the constructions of residential and commercial complex. For the analysis, the surveys conducted from 45 sites of reference streams within the Gap-Stream watershed and 3 regular sites during 2009 - 2010. Physical habitat health, based on the habitat model of Qualitative Habitat Evaluation Index(QHEI) declined from the headwaters(good - fair condition) to the downstream(poor condition). Chemical water quality, based turbidity and electric conductivity(EC), was degraded toward to the downstream, and especially showed abrupt increases, compared to the values of control streams(CS). Also, concentrations of chlorophyll-a in the downstreams were greater compared to the control stream(CS), indicating an eutrophication. Biological health conditions, based on the Index of Biological Integrity(IBI) using fish assemblages, averaged 19.3 which is judged as a fair condition by the biological criteria of the Ministry of Environment, Korea. The comparisons of model metric values in sensitive species and riffle-benthic species on the Maximum Species Richness Line(MSRL) of 45 reference streams indicated a massive disturbances in all sampling locations. Also, tolerance guild and trophic guild analyses suggest that dominances of tolerant species and omnivores were evident, indicating a biological degradation by habitat disturbances and organic matter pollutions. There was no distinct longitudinal variations of IBI model values from the headwater to the downstream in spite of slight chemical and habitat health gradients among the sampling sites. Overall, integrative ecological health(IEH) scores, based on the chemical, physical, and biological parameters, were low compared to the 45 reference streams due to physical and chemical disturbances of massive constructions of the residential and commercial complex. This stream, thus showed a tendency of typical urban streams which are disturbed in the chemical water quality, habitat structures, and biological integrity. Effective stream management plans and restoration strategies are required in this urban stream for improving integrative stream health.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4060-4079
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• 2020

Blur is an important type of image distortion. How to evaluate the quality of blurred image accurately and efficiently is a research hotspot in the field of image processing in recent years. Inspired by the multi-scale perceptual characteristics of the human visual system (HVS), this paper presents a no-reference image blur/sharpness assessment method based on multi-scale local features in the spatial domain. First, considering various content has different sensitivity to blur distortion, the image is divided into smooth, edge, and texture regions in blocks. Then, the Gaussian scale space of the image is constructed, and the categorized contrast features between the original image and the Gaussian scale space images are calculated to express the blur degree of different image contents. To simulate the impact of viewing distance on blur distortion, the distribution characteristics of local maximum gradient of multi-resolution images were also calculated in the spatial domain. Finally, the image blur assessment model is obtained by fusing all features and learning the mapping from features to quality scores by support vector regression (SVR). Performance of the proposed method is evaluated on four synthetically blurred databases and one real blurred database. The experimental results demonstrate that our method can produce quality scores more consistent with subjective evaluations than other methods, especially for real burred images.