• Title/Summary/Keyword: peak signal to noise ratio

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Multicasting Multiple Description Coding Using p-cycle Network Coding

  • Farzamnia, Ali;Syed-Yusof, Sharifah K.;Fisal, Norsheila
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.12
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    • pp.3118-3134
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    • 2013
  • This paper deliberates for a multimedia transmission scheme combining multiple description coding (MDC) and network coding (NC). Our goal is to take advantage from the property of MDC to provide quantized and compressed independent and identically distributed (iid) descriptions and also from the benefit of network coding, which uses network resources efficiently to recover lost data in the network. Recently, p-cycle NC has been introduced to recover and protect any lost or distorted descriptions at the receiver part exactly without need of retransmission. So far, MDC have not been explored using this type of NC. Compressed and coded descriptions are transmitted through the network where p-cycle NC is applied. P-cycle based algorithm is proposed for single and multiple descriptions lost. Results show that in the fixed bit rate, the PSNR (Peak Signal to Noise Ratio) of our reconstructed image and also subjective evaluation is improved significantly compared to previous work which is averaging method joint with MDC in order to conceal lost descriptions.

A Divide-Conquer U-Net Based High-Quality Ultrasound Image Reconstruction Using Paired Dataset (짝지어진 데이터셋을 이용한 분할-정복 U-net 기반 고화질 초음파 영상 복원)

  • Minha Yoo;Chi Young Ahn
    • Journal of Biomedical Engineering Research
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    • v.45 no.3
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    • pp.118-127
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    • 2024
  • Commonly deep learning methods for enhancing the quality of medical images use unpaired dataset due to the impracticality of acquiring paired dataset through commercial imaging system. In this paper, we propose a supervised learning method to enhance the quality of ultrasound images. The U-net model is designed by incorporating a divide-and-conquer approach that divides and processes an image into four parts to overcome data shortage and shorten the learning time. The proposed model is trained using paired dataset consisting of 828 pairs of low-quality and high-quality images with a resolution of 512x512 pixels obtained by varying the number of channels for the same subject. Out of a total of 828 pairs of images, 684 pairs are used as the training dataset, while the remaining 144 pairs served as the test dataset. In the test results, the average Mean Squared Error (MSE) was reduced from 87.6884 in the low-quality images to 45.5108 in the restored images. Additionally, the average Peak Signal-to-Noise Ratio (PSNR) was improved from 28.7550 to 31.8063, and the average Structural Similarity Index (SSIM) was increased from 0.4755 to 0.8511, demonstrating significant enhancements in image quality.

Low-complexity patch projection method for efficient and lightweight point-cloud compression

  • Sungryeul Rhyu;Junsik Kim;Gwang Hoon Park;Kyuheon Kim
    • ETRI Journal
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    • v.46 no.4
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    • pp.683-696
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    • 2024
  • The point cloud provides viewers with intuitive geometric understanding but requires a huge amount of data. Moving Picture Experts Group (MPEG) has developed video-based point-cloud compression in the range of 300-700. As the compression rate increases, the complexity increases to the extent that it takes 101.36 s to compress one frame in an experimental environment using a personal computer. To realize real-time point-cloud compression processing, the direct patch projection (DPP) method proposed herein simplifies the complex patch segmentation process by classifying and projecting points according to their geometric positions. The DPP method decreases the complexity of the patch segmentation from 25.75 s to 0.10 s per frame, and the entire process becomes 8.76 times faster than the conventional one. Consequently, this proposed DPP method yields similar peak signal-to-noise ratio (PSNR) outcomes to those of the conventional method at reduced times (4.7-5.5 times) at the cost of bitrate overhead. The objective and subjective results show that the proposed DPP method can be considered when low-complexity requirements are required in lightweight device environments.

Application of Deep Learning to Solar Data: 6. Super Resolution of SDO/HMI magnetograms

  • Rahman, Sumiaya;Moon, Yong-Jae;Park, Eunsu;Jeong, Hyewon;Shin, Gyungin;Lim, Daye
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.52.1-52.1
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    • 2019
  • The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

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Joint resource optimization for nonorthogonal multiple access-enhanced scalable video coding multicast in unmanned aerial vehicle-assisted radio-access networks

  • Ziyuan Tong;Hang Shen;Ning Shi;Tianjing Wang;Guangwei Bai
    • ETRI Journal
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    • v.45 no.5
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    • pp.874-886
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    • 2023
  • A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

Quality Enhancement for Hybrid 3DTV with Mixed Resolution Using Conditional Replenishment Algorithm

  • Jung, Kyeong-Hoon;Bang, Min-Suk;Kim, Sung-Hoon;Choo, Hyon-Gon;Kang, Dong-Wook
    • ETRI Journal
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    • v.36 no.5
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    • pp.752-760
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    • 2014
  • This paper proposes a conditional replenishment algorithm (CRA) to improve the visual quality (where spatial resolutions of the left and right views are mismatched) of a hybrid stereoscopic 3DTV that is based on the ATSC-M/H standard. So as to generate an enhanced view, the CRA is to choose the better substitute among a disparity-compensated view with high quality and a simply interpolated view. The CRA generates a disparity map that includes modes and disparity vectors as additional information. It also employs a quad-tree structure with variable block size by considering the spatial correlation of disparity vectors. In addition, it takes advantage of the disparity map used in a previous frame to keep the amount of additional information as small as possible. The simulation results show that the proposed CRA can successfully improve the peak signal-to-noise ratio of a poor-quality view and consequently have a positive effect on the subjective quality of the resulting 3D view.

Rate control to reduce bitrate fluctuation on HEVC

  • Yoo, Jonghun;Nam, Junghak;Ryu, Jiwoo;Sim, Donggyu
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.3
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    • pp.152-160
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    • 2012
  • This paper proposes a frame-level rate control algorithm for low delay video applications to reduce the fluctuations in the bitrate. The proposed algorithm minimizes the bitrate fluctuations in two ways with minimal coding loss. First, the proposed rate control applies R-Q model to all frames including the first frame of every group of pictures (GOP) except for the first one of a sequence. Conventional rate control algorithms do not use any R-Q models for the first frame of each GOP and do not estimate the generated-bit. An unexpected output rate result from the first frame affects the remainder of the pictures in the rate control. Second, a rate-distortion (R-D) cost is calculated regardless of the hierarchical coding structure for low bitrate fluctuations because the hierarchical coding structure controls the output bitrate in rate distortion optimization (RDO) process. The experimental results show that the average variance of per-frame bits with the proposed algorithm can reduce by approximately 33.8% with a delta peak signal-to-noise ratio (PSNR) degradation of 1.4dB for a "low-delay B" coding structure and by approximately 35.7% with a delta-PSNR degradation of 1.3dB for a "low-delay P" coding structure, compared to HM 8.0 rate control.

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Enhanced UV-Visible Absorbance Detection in Capillary Electrophoresis Using Modified T-Shaped Post-Column Flow Cell

  • Lim, Kwan-Seop;Kim, Su-Hyeon;Hahn, Jong-Hoon
    • Bulletin of the Korean Chemical Society
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    • v.23 no.2
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    • pp.295-300
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    • 2002
  • The construction of the T-shaped post-column flow cell has been changed to enhance the practicability as a UV-visible absorbance detector for capillary electrophoresis. In this new design, a rectangular cube-shaped inner structure is employed, which completely fits the outer rectangular tubing. This arrangement has greatly facilitated the fabrication of the T-cells. In addition, the volume for the auxiliary flow has been dramatically reduced down to 300 ${\mu}L$, and its volume flow rate is optimized at 4.2 ${\mu}L$/min. The short optical path length in the sheath flows (500 ${\mu}m$ on each side) minimizes background absorption, and thus enhances its performance in low-UV wavelengths. We have optimized the auxiliary flow rate at 50 ${\mu}m$/s, so that migration times are insensitive to the flow rate. This optimization has improved repeatabilities in migration times and peak heights. A double-beam detection scheme using a pair of photodiodes is employed to increase the signal-to-noise ratio.

Selective Quality Control of Multiple Video Programs for Digital Broadcasting Service (디지털 방송 서비스를 위한 다수의 비디오 프로그램들의 선택적 화질 제어)

  • 홍성훈;유상조
    • Journal of Broadcast Engineering
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    • v.6 no.2
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    • pp.148-159
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    • 2001
  • This paper presents a selective duality control system to control relative picture quality among the video programs in terms of Peak Signal-to-Noise Ratio (PSNR) . The selective quality control system allows variable bit rate (VBR) for each video program to maintain the pre-determitted relative picture Quality among aggregated video programs while keeping a constant bit rate for alt programs to be transmitted over a single constant bit rate (CBR) channel. Thus is achieved by simultaneous controlling the video encoders to generate VBR video streams at the central controller. furthermore, we also suggest a buffer regulation method based on the analysis of the constraints Imposed by sender/receiver buffer sizes and the total transmission rate. Through various simulation results, it is found that the proposed quality control system guarantees that the video buffers neither overflow nor underflow and the quality control errors do not exceed 0.1 dB.

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The Determination of Dopamine in the Presence of Ascorbic Acid at the Modified Glassy Carbon Electrode with Phytic Acid and Single-Walled Carbon Nanotubes

  • Bae, Si-Ra;Jeong, Hae-Sang;Jeon, Seung-Won
    • Bulletin of the Korean Chemical Society
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    • v.28 no.12
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    • pp.2363-2368
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    • 2007
  • A glassy carbon electrode (GCE) modified with phytic acid (PA) and single-walled carbon nanotubes (SWNTs) were investigated by voltammetric methods in buffer solution. The PA-SWNTs/GCE-modified electrode demonstrated substantial enhancements in electrochemical sensitivity and selectivity towards dopamine (DA) in the presence of L-ascorbic acid (AA). The PA-SWNTs films promoted the electron transfer reaction of DA, while the PA film, acting as a negatively charged linker, combined with the positively charged DA to induced DA accumulation in the film at pH under 7.4. However, the PA film restrained the electrochemical response of the negatively charged AA due to the electrostatic repulsion. The anodic peak potentials of DA and AA could be separated by electrochemical techniques, and the interferences from AA were effectively eliminated in the DA determination. Linear calibration plots were obtained in the DA concentration range of 0.1-10 μM and the detection limit of the DA oxidation current was determined to be 0.06 μM at a signal-to-noise ratio of 3. The results indicated that the modified electrode is used to determine DA without interference from AA.