• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.241-242
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• 2006

MPEG Surround is an audio coding technology that represents multi-channel audio signal with downmixed audio signal(s) and very low bitrate side information based on Binaural Cue Coding. The side information consists of Inter-Channel Level Difference, Inter-Channel Correlation, and payloads. These two parameters are correspondent to the well-known spatial parameters in psycho-acoustics, Inter-aural Level Difference (ILD) and Inter-Aural Cross Correlation (IACC). Though ICLD is to provide perceptually equivalent ILD to the listener, however, the ILD of the original multi-channel audio signal and that of the MPEG Surround encoded signal was different. The difference between two ILD values is defined as ILD Distortion (ILDD). This paper provides how ILDD can be applied to enhance sound quality in MPEG Surround and how much ILDD is decreased.

• Journal of Multimedia Information System
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• v.9 no.2
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.655-670
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• 2010

To be reversible as a data hiding method, the original content and hidden message should be completely recovered. One important objective of this approach is to achieve high embedding capacity and low distortion. Using predicted errors is very effective for increasing the embedding capacity. Sorting the predicted errors has a good influence on decreasing distortion. In this paper, we present an improved reversible data hiding scheme using upgraded histogram shifting based on sorting the predicted errors. This new scheme is characterized by the algorithm which is able to find the optimum threshold values and manage the location map effectively. Experimental results compared with other methods are presented to demonstrate the superiority of the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.15-20
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• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.143-150
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• 2005

Camera image is very sensitive to illumination that result in difficulties for recognizing character. Also Camera captured document images have not only skew but also vignetting effect and geometric distortion. Vignetting effect make it difficult to separate characters from the document images. Geometric distortion, occurred by the mismatch of angle and center position between the document image and the camera, make the shape of characters to be distorted, so that the character recognition is more difficult than the case of using scanner. In this paper, we propose a method that can increase the performance of character recognition by correcting the geometric distortion of document images using a linear approximation which changes the quadrilateral region to the rectangle one. The proposed method also determine the quadrilateral transform region automatically, using the alignment of character lines and the skewed angles of characters located in the edges of each character line. Proposed method, therefore, can correct the geometric distortion without getting positional information from camera.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1684-1690
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• 2018

A new digital pre-distortion (DPD) technique for closely spaced dual-band signals is proposed. In the system under consideration, dual-band signals are amplified by a single broadband power amplifier (PA) at a transmitter. The PA output is distorted by cross-modulation between the two bands as well as their own inter-modulation distortion. Especially, if the two bands are placed in close proximity to each other, their spectral regrowths due to in-band intermodulation overlap with each other, which degrades DPD performance. To solve this problem, we propose a new DPD technique where the dual-band PA characteristics are estimated first, and then the DPD parameters are obtained from the estimated PA characteristics. By finding the DPD parameters through two steps, pre-distortion can perform well for the closely-spaced dual band signals. The proposed technique is verified through computer simulation. Simulation result shows that the proposed method performs better than the conventional method for closely-spaced dual band signals.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.882-897
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• 2020

Recently, the use of immersive media contents representing Panorama and 360° video is increasing. Since the viewing angle is limited to generate the content through a general camera, image stitching is mainly used to combine images taken with multiple cameras into one image having a wide field of view. However, if the parallax between the cameras is large, parallax distortion may occur in the stitched image, which disturbs the user's content immersion, thus an image stitching overcoming parallax distortion is required. The existing Seam Optimization based image stitching method to overcome parallax distortion uses energy function or object segment information to reflect the location information of objects, but the initial seam generation location, background information, performance of the object detector, and placement of objects may limit application. Therefore, in this paper, we propose an image stitching method that can overcome the limitations of the existing method by adding a weight value set differently according to the type of object to the energy value using object detection based on deep learning.

• Journal of Information Display
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• v.12 no.4
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• pp.195-198
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• 2011

Proposed herein is a flexible bistable chiral splay nematic display mode with an enhanced memory retention time under external distortion. By adopting the polymerized reactive-mesogen structure mixed in a liquid crystal layer, local anchoring energy is generated on the boundary between the polymer structures, and the relaxation from the ${\pi}$-twisted state to the initial splay state could be interrupted. As a result, the memory retention time becomes significantly longer, and the stability against the external distortion is enhanced.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.979-982
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• 2002

Compressing image data by using Vector Quantization (VQ)［1］-［3］will compare Training Vectors with Codebook. The result is an index of position with minimum distortion. The implementing Random Codebook will reduce the image quality. This research presents the Splitting solution ［4］,［5］to implement the Codebook, which improves the image quality［6］by the average Training Vectors, then splits the average result to Codebook that has minimum distortion. The result from this presentation will give the better quality of the image than using Random Codebook.