• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.63-71
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• 2009

In this paper, a new low-complexity distortion estimation method for H.264 rate-distortion optimized mode decision is proposed. The coding processes, such as DCT, quantization, inverse quantization, inverse DCT, and reconstruction are needed to compute the distortion in an H.264 encoder. To reduce these processes, we estimate distortion using integer operations with coefficients obtained in the quantization process. Inverse quantization, inverse DCT, and reconstruction processes are not needed by the proposed method. For quantization parameters 24 to 36, experimental results show that the time saving of rate-distortion optimized mode decision is on average 29 % and as high as 42 % with negligible degradation in coding performance.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.251-257
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• 2006

The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization)and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortion

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.74-80
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• 2012

In resolution-constrained quantization, the size of Voronoi cell varies depending on probability density function of the input data, which causes large amount of distortion outliers. We propose a vector quantization method that reduces distortion outliers by combining the generalized Lloyd algorithm (GLA) and the cell-size constrained vector quantization (CCVQ) scheme. The training data are divided into the inside and outside regions according to the size of Voronoi cell, and consequently CCVQ and GLA are applied to each region, respectively. As CCVQ is applied to the densely populated region of the source instead of GLA, the number of centroids for the outside region can be increased such that distortion outliers can be decreased. In real-world environment, source mismatch between training and test data is inevitable. For the source mismatch case, the proposed algorithm improves performance in terms of average distortion and distortion outliers.

• 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.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.18-25
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• 2017

Recently, VR HMD (virtual reality head mounted display) has been utilized for virtual training, entertainment, vision therapy, and optometry. In particular, virtual reality contents are increasingly used for vision therapy and optometry. Accordingly, high-quality virtual reality contents such as a natural vision of life is required. Therefore, it is necessary to study the content production according to the optical characteristics of the VR HMD. The purpose of this paper is to suggest a proper FOV (field of view) of contents according to the distortion rate. We produced virtual reality contents and obtained distorted images by virtual camera. The distortion rate is calculated by using the distorted image. It is proved that the optimal FOV of the VR content with the minimum distortion is $90{\sim}100^{\circ}$. The results of this study are expected to be applied to the production of high quality contents.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.587-599
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• 1996

In general fractal imge compression, each range block is approximated by a contractive transform of the matching domain block under the mean squared error criterion. In this paper, a distortion measure reflecting the properties of human visual system is defined and applied to a fractal image compression. the perceptual distortion measure is obtained by multiplying the mean square error and the noise sensitivity modeled by using the background brightness and spatial masking. In order to compare the performance of the mean squared error and perceptual distortion measure, a simulation is carried out by using the 512*512 Lena and papper gray image. Compared to the results, 6%-10% compression ratio improvements under improvements under the same image quality are achieved in the perceptual distortion measure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1052-1063
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• 1999

In designing the quantizer of a coding scheme using a training sequence (TS), the training algorithm tries to find a quantizer that minimizes the distortion measured in the TS. In order to evaluate the trained quantizer or compare the coding scheme, we can observe the minimized distortion. However, the minimized distortion is a biased estimate of the minimal distortion for the input distribution. Hence, we could often overestimate a quantizer or make a wrong comparison even if we use a validating sequence. In this paper, by compensating the minimized distortion for the TS, a new estimate is proposed. Compensating term is a function of the training ratio, the TS size to the codebook size. Several numerical results are also introduced for the proposed estimate.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.131-137
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• 2013

The barrel distortion makes serious problems in a wide-angle camera employing a lens of a short focal length. This paper presents a low-complexity hardware architecture for a real-time barrel distortion corrector and its implementation. In the proposed barrel distortion corrector, the conventional algorithm is modified so that the correction is performed incrementally, which results in the reduction of the number of required hardware modules for the distortion correction. The proposed barrel distortion corrector has a pipelined architecture so as to achieve a high-throughput correction. The correction rate is 74.86 frames per sec at the operating frequency of 314MHz in a $0.11{\mu}m$ CMOS process, where the frame size is $2048{\times}2048$. The proposed barrel distortion corrector is implemented with 14.3K logic gates.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.24-30
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• 1984

Group delay distortion (phase distortion) is a characteristic which is of no account from a standpoint of voice transmission. But this distortion becomes the major source of distortion in wave form transmission such as data, FAX and others over the public switching telephone network (voice band transmission) so that it must be drastically studied. This paper makes analysis of group deray distortion of the telephone network, describs experimental and measuring results and refers also to the improvement of distortion for the purpose of opening the public switching telephone network to data transmission.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.316-321
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• 2001

When the multiple video sources are together transmitted through the channel of fixed bandwidth, the efficiently picture quality method is necessary. This paper presents the picture quality control method to keep the same distortion level among the video sources. We first find a model of distortion and bitrate for the multiplexing system of multiple sources. Then we obtain the bitrate for each source to have same distortion level among the sources by using the approximated model parameters for simple implementation.