• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.425-433
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• 2018

In this paper, we propose a super-resolution reconstruction algorithm for plenoptic images based on the reliability of disparity. The subperture image generated by the Flanoptic camera image is used for disparity estimation and reconstruction of super-resolution image based on TV_L1 algorithm. In particular, the proposed image reconstruction method is effective in the boundary region where disparity may be relatively inaccurate. The determination of reliability of disparity vector is based on the upper, lower, left and right positional relationship of the sub-aperture image. In our method, the unreliable vectors are excluded in reconstruction. The performance of the proposed method was evaluated by comparing to a bicubic interpolation method, a conventional disparity based method and dictionary based method. The experimental results show that the proposed method provides the best performance in terms of PSNR(Peak Signal to noise ratio), SSIM(Structural Similarity).

• Journal of Digital Policy
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• v.2 no.3
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• pp.1-7
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• 2023

In this paper, I proposes a method for performing single image super resolution by separating texture-spatial domains and then classifying features based on detailed information. In CNN (Convolutional Neural Network) based super resolution, the complex procedures and generation of redundant feature information in feature estimation process for enhancing details can lead to quality degradation in super resolution. The proposed method reduced procedural complexity and minimizes generation of redundant feature information by splitting input image into two channels: texture and spatial. In texture channel, a feature refinement process with step-wise skip connections is applied for detail restoration, while in spatial channel, a method is introduced to preserve the structural features of the image. Experimental results using proposed method demonstrate improved performance in terms of PSNR and SSIM evaluations compared to existing super resolution methods, confirmed the enhancement in quality.

• Journal of Digital Policy
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• v.3 no.1
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• pp.27-32
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• 2024

In this paper, proposes a super resolution method that enhances the quality of results by refining texture features, contrasting each, and utilizing the results as weights. For the improvement of quality, a precise and clear restoration result in details such as boundary areas is crucial in super resolution, along with minimizing unnecessary artifacts like noise. The proposed method constructs a residual block structure with multiple paths and skip-connections for feature estimation in conventional Convolutional Neural Network (CNN)-based super resolution methods to enhance quality. Additional learning is performed for sharpened and blurred image results for further texture analysis. By contrasting each super resolution result and allocating weights through this process, the proposed method achieves improved quality in detailed and smoothed areas of the image. The experimental results of the proposed method, evaluated using the PSNR and SSIM values as quality metrics, show higher results compared to existing algorithms, confirming the enhancement in quality.

• Journal of Broadcast Engineering
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• v.14 no.5
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• pp.573-588
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• 2009

In this paper, we propose a novel video quality degradation monitoring scheme titled VR-VQMS(Visual Rhythm based Video Quality Monitoring Scheme) over an IPTV service prone to packet losses during network transmission. Proposed scheme quantifies the amount of quality degradation due to packet losses, and can be classified into a RR(reduced-reference) based quality measurement scheme exploiting visual rhythm data of H.264-encoded video frames at a media server and reconstructed ones at an Set-top Box as feature information. Two scenarios, On-line and Off-line VR-VQMS, are proposed as the practical solutions. We define the NPSNR(Networked Peak-to-peak Signal-to-Noise Ratio) modified by the well-known PSNR as a new objective quality metric, and several additional objective and subjective metrics based on it to obtain the statistics on timing, duration, occurrence, and amount of quality degradation. Simulation results show that the proposed method closely approximates the results from 2D video frames and gives good estimation of subjective quality(i.e.,MOS(mean opinion score)) performed by 10 test observers. We expect that the proposed scheme can play a role as a practical solution to monitor the video quality experienced by individual customers in a commercial IPTV service, and be implemented as a small and light agent program running on a resource-limited set-top box.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.78-84
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• 2009

In general video coding systems, motion estimation (ME) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. Fractional pixel motion estimation can improve the video compression rate at the cost of higher computational complexity. It is based on the experimental results that the sum of absolute differences (SAD) shows parabolic shape and thus can be approximated by using interpolation technique. In this paper, we propose a fast fractional pixel search algorithm by combining SASR (Simplified Adaptive Search Range) and the CBCDS (Center Biased Cross-Diamond Search) pattern with the predicted motion vector. Compare with the fractional pel full search and the CBFPS, the proposed CBCDS algorithms can reduce fractional pel search points up to 81.4%, respectively with the PSNR lost about 0.05dB.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.45-50
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• 2010

An image interpolation is a technique to use for enhancement of image resolution, it have two problems which are image quality degradation of the interpolated result image and high computation complexity. In this paper, to solve the problem, we propose an image interpolation algorithm using loss information estimation and implement the proposed method on portable device. From reduction image of obtained low resolution image, the proposed method can computes error to use image interpolated and estimate loss information by interpolation of the computed error. The estimated loss information is added to interpolated high resolution image with weight factor. We verified that the proposed method has improved FSNR as 2dB than conventional algorithms by experiments. Also, we implemented the proposed method on portable device and checked up real-time action. The proposed algorithm may be helpful for various application for image enlargement and reconstruction.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.553-560
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• 2003

Since Wavelet Transform decomposes a video frame into subbands with various frequencies and resolutions, the reconstructed video qualify at a receiver fluctuates according to the location of transmission errors within frames. This deteriorates the whole visual duality of the video. Specifically, for a wavelet based video which exploits the motion estimation prediction scheme, the transmission errors of a subband not only have a bad effect on other subbands within a same frame but also propagates to the subsequent frames. In this paper, we propose BDP(Block Based Dispersive Packetization) scheme, for a wavelet based video stream, which maintains constant video quality despite packet location that a transmission error occurs. To evaluate the performance of the proposed scheme, we use MRME(Multi-Resolution Motion Estimation) scheme to compress a video in Inter coding mode and Gilbert´s error model to generate the error patterns in wireless network environment. The simulation results show that BDP is more efficient than BP (Block based Packetization) or DP (Dispersive Packetization) in both PSNR and visual quality.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.181-197
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• 2003

Notion Compensation(MC) technique using Sub-Band Coding with the hierarchical structure is efficient to estimate real motion. In the hierarchical pyramid method, low-band MC pyramid method is popular, where the upper layer estimate the glover motion and next lower layer estimate the local motion. The low-band MC pyramid scheme has two problems. First, because the quantization errors at lower layer are accumulated when using coding and quantizing, it is impossible to search the exact Motion Vector(MV) Second, because of the top-down search problem in the hierarchical structure, MV mismatch in upper layer causes serious MV in lower layer So. we propose new hierarchical MC pyramid method based on edge classification. In this Paper, we show that the performance of proposed Pass-band motion compensation pyramid technique is better than low-band motion compensation pyramid. Also, in the pyramid motion estimation, we propose initial MV estimation scheme based on the edge-pattern classification. As a result, we find that PSNR was increased.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.653-660
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• 2004

Object-oriented analysis-synthesis coding (OOASC) subdivides each image of a sequence into a number of moving objects and estimates and compensates the motion of each object. It employs a motion parameter technique for estimating motion information of each object. The motion parameter technique employing gradient operators requires a high computational load. The main objective of this paper is to present efficient motion parameter estimation techniques using the hierarchical structure in object-oriented analysis-synthesis coding. In order to achieve this goal, this paper proposes two algorithms : hybrid motion parameter estimation method (HMPEM) and adaptive motion parameter estimation method (AMPEM) using the hierarchical structure. HMPEM uses the proposed hierarchical structure, in which six or eight motion parameters are estimated by a parameter verification process in a low-resolution image, whose size is equal to one fourth of that of an original image. AMPEM uses the same hierarchical structure with the motion detection criterion that measures the amount of motion based on the temporal co-occurrence matrices for adaptive estimation of the motion parameters. This method is fast and easily implemented using parallel processing techniques. Theoretical analysis and computer simulation show that the peak signal to noise ratio (PSNR) of the image reconstructed by the proposed method lies between those of images reconstructed by the conventional 6- and 8-parameter estimation methods with a greatly reduced computational load by a factor of about four.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.54-63
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• 2000

We present a multi-resolution block matching algorithm (BMA) for fast motion estimation At the coarsest level, a motion vector (MV) having minimum matching error is chosen via a full search, and a MV with minimum matching error is concurrently found among the MVs of the spatially adjacent blocks Here, to examine the spatial MVs accurately, we propose an efficient method for searching full resolution MV s without MV quantization even at the coarsest level The chosen two MV s are used as the initial search centers at the middle level At the middle level, the local search is performed within much smaller search area around each search center If the method used at the coarsest level is adopted here, the local searches can be done at integer-pel accuracy A MV having minimum matching error is selected within the local search areas, and then the final level search is performed around this initial search center Since the local searches are performed at integer-pel accuracy at the middle level, the local search at the finest level does not take an effect on the overall performance So we can skip the final level search without performance degradation, thereby the search speed increases Simulation results show that in comparison with full search BMA, the proposed BMA without the final level search achieves a speed-up factor over 200 with minor PSNR degradation of 02dB at most, under a normal MPEG2 coding environment Furthermore, our scheme IS also suitable for hardware implementation due to regular data-flow.