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41 results on '"Wang Xiaotao"'

1. NTIRE 2023 Challenge on Night Photography Rendering

Author

Shutova, Alina, primary, Ershov, Egor, additional, Perevozchikov, Georgy, additional, Ermakov, Ivan, additional, Banić, Nikola, additional, Timofte, Radu, additional, Collins, Richard, additional, Efimova, Maria, additional, Terekhin, Arseniy, additional, Zini, Simone, additional, Rota, Claudio, additional, Buzzelli, Marco, additional, Bianco, Simone, additional, Schettini, Raimondo, additional, Lei, Chunxia, additional, Wang, Tingniao, additional, Wang, Song, additional, Liu, Shuai, additional, Feng, Chaoyu, additional, Shao, Guangqi, additional, Wang, Hao, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Xu, Lu, additional, Zhang, Chao, additional, Wang, Yasi, additional, Guo, Jin, additional, Sun, Yangfan, additional, Liu, Tianli, additional, Hao, Dejun, additional, Kınlı, Furkan, additional, Özcan, Barış, additional, Kıraç, Furkan, additional, Chung, Hyerin, additional, Lee, Nakyung, additional, Kwak, Sung Keun, additional, Conde, Marcos, additional, Seizinger, Tim, additional, Vasluianu, Florin, additional, Elezabi, Omar, additional, Hsieh, Chia-Hsuan, additional, Chen, Wei-Ting, additional, Yang, Hao-Hsiang, additional, Huang, Zhi-Kai, additional, Chang, Hua-En, additional, Chen, I-Hsiang, additional, Chen, Yi-Chung, additional, and Chiang, Yuan-Chun, additional

Published
2023
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2. MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results

Author

Dai, Yuekun, primary, Li, Chongyi, additional, Zhou, Shangchen, additional, Feng, Ruicheng, additional, Zhu, Qingpeng, additional, Sun, Qianhui, additional, Sun, Wenxiu, additional, Loy, Chen Change, additional, Gu, Jinwei, additional, Liu, Shuai, additional, Wang, Hao, additional, Feng, Chaoyu, additional, Wang, Luyang, additional, Shao, Guangqi, additional, Zhang, Chenguang, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Zhang, Dafeng, additional, Kong, Xiangyu, additional, Liu, Guanqun, additional, Bai, Mengmeng, additional, Ouyang, Jia, additional, Wang, Xiaobing, additional, Yuan, Jiahui, additional, Li, Xinpeng, additional, Jiang, Chengzhi, additional, Jiang, Ting, additional, Lin, Wenjie, additional, Wu, Qi, additional, Han, Mingyan, additional, Luo, Jinting, additional, Yu, Lei, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Yan, Bo, additional, Li, Zhuang, additional, Li, Yadong, additional, Wang, Hongbin, additional, Song, Soonyong, additional, Fu, Minghan, additional, Khan, Rayyan Azam, additional, Wu, Fangxiang, additional, Zhang, Zhao, additional, Zhao, Suiyi, additional, Zheng, Huan, additional, Gao, Yangcheng, additional, Wei, Yanyan, additional, Ren, Jiahuan, additional, Wang, Bo, additional, Luo, Yan, additional, Gao, Shuaibo, additional, Wu, Wenhui, additional, Kang, Sicong, additional, Akalwadi, Nikhil, additional, Raichur, Ankit, additional, Patil, Vinod, additional, G, Allabakash, additional, A, Swaroop, additional, Joshi, Amogh, additional, Desai, Chaitra, additional, Tabib, Ramesh Ashok, additional, Patil, Ujwala, additional, Sicheng Li, Uma Mudenagudi, additional, Zhu, Ruoxi, additional, Lian, Jiazheng, additional, Xu, Shusong, additional, Liu, Zihao, additional, Nathan, Sabari, additional, and Kansal, Priya, additional

Published
2023
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3. NTIRE 2023 Video Colorization Challenge

Author

Kang, Xiaoyang, primary, Lin, Xianhui, additional, Zhang, Kai, additional, Hui, Zheng, additional, Xiang, Wangmeng, additional, He, Jun-Yan, additional, Li, Xiaoming, additional, Ren, Peiran, additional, Xie, Xuansong, additional, Timofte, Radu, additional, Yang, Yixin, additional, Pan, Jinshan, additional, Zheng, Zhong, additional, Qiyan, Peng, additional, Jiangxin, Zhang, additional, Jinhui, Dong, additional, Jinjing, Tang, additional, Chichen, Li, additional, Li, Lin Qipei, additional, Liang, Qirong, additional, Gang, Ruipeng, additional, Liu, Xiaofeng, additional, Feng, Shuang, additional, Liu, Shuai, additional, Wang, Hao, additional, Feng, Chaoyu, additional, Bai, Furui, additional, Zhang, Yuqian, additional, Shao, Guangqi, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Chen, Siqi, additional, Zhang, Yu, additional, Xu, Hanning, additional, Liu, Zheyuan, additional, Zhang, Zhao, additional, Luo, Yan, additional, and Zuo, Zhichao, additional

Published
2023
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4. NTIRE 2023 Challenge on Image Denoising: Methods and Results

Author

Li, Yawei, primary, Zhang, Yulun, additional, Timofte, Radu, additional, Gool, Luc Van, additional, Tu, Zhijun, additional, Du, Kunpeng, additional, Wang, Hailing, additional, Chen, Hanting, additional, Li, Wei, additional, Wang, Xiaofei, additional, Hu, Jie, additional, Wang, Yunhe, additional, Kong, Xiangyu, additional, Wu, Jinlong, additional, Zhang, Dafeng, additional, Zhang, Jianxing, additional, Liu, Shuai, additional, Bai, Furui, additional, Feng, Chaoyu, additional, Wang, Hao, additional, Zhang, Yuqian, additional, Shao, Guangqi, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Xu, Rongjian, additional, Zhang, Zhilu, additional, Chen, Yunjin, additional, Ren, Dongwei, additional, Zuo, Wangmeng, additional, Wu, Qi, additional, Han, Mingyan, additional, Cheng, Shen, additional, Li, Haipeng, additional, Jiang, Ting, additional, Jiang, Chengzhi, additional, Li, Xinpeng, additional, Luo, Jinting, additional, Lin, Wenjie, additional, Yu, Lei, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Arora, Aditya, additional, Zamir, Syed Waqas, additional, Vazquez-Corral, Javier, additional, Derpanis, Konstantinos G., additional, Brown, Michael S., additional, Li, Hao, additional, Zhao, Zhihao, additional, Pan, Jinshan, additional, Dong, Jiangxin, additional, Tang, Jinhui, additional, Yang, Bo, additional, Chen, Jingxiang, additional, Li, Chenghua, additional, Zhang, Xi, additional, Zhang, Zhao, additional, Ren, Jiahuan, additional, Ji, Zhicheng, additional, Miao, Kang, additional, Zhao, Suiyi, additional, Zheng, Huan, additional, Wei, YanYan, additional, Liu, Kangliang, additional, Du, Xiangcheng, additional, Liu, Sijie, additional, Zheng, Yingbin, additional, Wu, Xingjiao, additional, Jin, Cheng, additional, Irny, Rajeev, additional, Koundinya, Sriharsha, additional, Kamath, Vighnesh, additional, Khandelwal, Gaurav, additional, Khowaja, Sunder Ali, additional, Yoon, Jiseok, additional, Lee, Ik Hyun, additional, Chen, Shijie, additional, Zhao, Chengqiang, additional, Yang, Huabin, additional, Zhang, Zhongjian, additional, Huang, Junjia, additional, and Zhang, Yanru, additional

Published
2023
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17. Context-aware event-driven stereo matching

Author

Zou, Dongqing, primary, Guo, Ping, additional, Wang, Qiang, additional, Wang, Xiaotao, additional, Shao, Guangqi, additional, Shi, Feng, additional, Li, Jia, additional, and Park, Paul-K.J., additional

Published
2016
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19. Maximum Correntropy Criterion-Based Low-Rank Preserving Projection for Hyperspectral Image Classification.

Author

Wang, Xiaotao and Liu, Fang

Abstract

In this letter, we propose a maximum correntropy criterion-based low-rank preserving projection (MCC-LRPP) for hyperspectral image (HSI) classification, seeking a low-dimensional subspace via low-rank correntropy graph where spectral band structure can be preserved as much as possible. Unlike the sparse and low-rank-based techniques available, MCC-LRPP introduces maximum correntropy criteria (MCC) to model individual band reconstruction error and noise discriminately instead of $l_{2}$ and Frobenius related norms. It is equivalent to a row-weighting regularization problem. It puts more emphasis on bands with less noise and indirectly increase their importance and vice versa. MCC-LRPP enhances band difference and thus preserves their local structure as well as global structure. Indeed, more local structure means more discriminant ability. The experimental results on several popular HSI data sets prove its effectiveness and superiority when compared to other existing dimension reduction means. [ABSTRACT FROM AUTHOR]

Published
2018
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21. Design of a Composite Video Signal for DVD Recorder Measurement System Based on Virtual Instrument Technology

Author

Wang Jizhou, Liu Hongbo, Xu Zhixiang, and Wang Xiaotao

Subjects
NTSC, Signal generator, Computer science, business.industry, Video capture, S-Video, DVD recorder, Video processing, business, Signal, Computer hardware, Composite video
Abstract

In this paper, a new source video signal is designed for online DVD evaluation and then its composite video signal waveform is produced through a video waveform generator board PXI-5431. The composite video field, no matter NTSC or PAL system it is, includes both visible image and invisible lines. The visible image has been set to different patterns, and the invisible lines include three lines such as copy once, auto clock setting and electronic program guide. Detailed procedures to produce both parts are well illustrated and the virtual instrument blocks in G-language are also presented.

Published
2007
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22. Online Measurement System for DVD Recorder and its Video Signal Deficiency Analysis

Author

Wang Xiaotao, Zhou Yuanli, Xu Zhixiang, and Sun Rihe

Subjects
Video recording, Workstation, Virtual instrumentation, business.industry, law, Computer science, System of measurement, DVD recorder, business, Signal, Computer hardware, Virtual instrument, law.invention
Abstract

This paper firstly focuses on the video signal measurement system for DVD recorder, one of the most demanding tasks for DVD recorders manufacturing. An online measurement system is configured and set up by PC workstation and LabVIEW, a virtual instrument development platform. After that, the system is put into practice successfully. Some deficient video signals are captured and their image and waveforms are illustrated. The causes behind the deficiency are further analyzed. The online measurement system becomes an essential tool to guarantee the quality of DVD recorders before packing.

Published
2007
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23. Local Image Color Components Analysis Method and its Application in Online DVD Recorder Measurement

Author

Wang Xiaotao, Xu Zhixiang, Liu Liang, and Ma Qiang

Subjects
Measure (data warehouse), Pixel, Virtual instrumentation, Image quality, Color image, Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, DVD recorder, Image (mathematics), Computer graphics (images), Computer vision, Artificial intelligence, business, Analysis method
Abstract

During manufacturing DVD recorders, it is necessary to measure the loss between original and play-back video signals, so as to evaluate the output image quality of video channels. This paper presents a local image color components analysis method to analyze the sampled image in a very limited time. A local image area, sized 20times20 pixel, is carefully selected. Its RBG components are calculated and the method is illustrated and coded under the virtual instrument environment LabVIEW and TestStand. Examples are given to demonstrate its feasibility.

Published
2007
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24. Weighted Low-Rank Representation-Based Dimension Reduction for Hyperspectral Image Classification.

Author

Wang, Xiaotao and Liu, Fang

Abstract

A predimension-reduction algorithm that couples weighted low-rank representation (WLRR) with a skinny intrinsic mode functions (IMFs) dictionary is proposed for hyperspectral image (HSI) classification. It seeks a low-rank subspace to solve the performance degradation issue encountered by linear discriminant analysis in a small-sample-size situation. It can also improve the scatter matrix estimation when using a large training set. Unlike those commonly used methods, e.g., the principal component analysis-based ones, WLRR focuses on preserving more structure information. Based on the traditional LRR model, WLRR introduces a local weighted regularization to characterize the correlation between samples such that HSI-specific local structure can be better preserved as well as its global structure. Indeed, more structure information gives more additional discriminant ability. Furthermore, a new discriminant IMFs dictionary is designed to enhance interclass difference via empirical mode decomposition. The proposed method is investigated on several HSI data sets. All experimental results prove it a competitive and promising predimension-reduction means when compared to other traditional techniques. [ABSTRACT FROM PUBLISHER]

Published
2017
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37. A Depth-First ML Decoding Algorithm for Tail-Biting Trellises.

Author

Qian, Hua, Wang, Xiaotao, Kang, Kai, and Xiang, Weidong

Subjects
*DATA packeting, *PACKET switching, *SEARCH algorithms, *TELECOMMUNICATION, *DATA transmission systems
Abstract

Tail-biting codes are efficient for short data packets by eliminating the rate loss in conventional known-tail codes. The existing maximum-likelihood (ML) decoding algorithms, such as the Viterbi heuristic ML decoder (VH ML decoder) and the trap detection-based ML decoder (TD-ML decoder), have to visit each state of the tail-biting trellis at least once. The decoding efficiency of these decoding algorithms can be improved further. In this paper, we propose an ML decoder for tail-biting trellises with bounded searches (BSs). We first perform a unidirectional bounded searching algorithm to estimate the lower bound of path metric of tail-biting paths on each sub-tail-biting trellis and exclude impossible candidates of starting states. In the second phase, a bidirectional searching algorithm is applied to find the ML tail-biting (MLTB) path on the survivor sub-tail-biting trellises. The proposed algorithm exhibits lower decoding complexity floor than other existing algorithms on tail-biting trellis. Simulation results for the (24, 12, 8) Golay codes and Eb/N0=\5\ \dB show that, for the proposed ML decoder, the average number of visited states per decoded bit is less than 2, whereas the average number of visited states per decoded bit is more than 12 for the VH ML decoder. [ABSTRACT FROM PUBLISHER]

Published
2015
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39. Wet chemical etching silicon wafer with low-reflection and super-hydrophobicity.

Author

Wuxing Lai, Wang, Xiaotao, Tielin Shi, Wei Zhang, and Zirong Tang

Abstract

Successful etching silicon wafer for solar cells has been already prepared. In this work, wet chemical etching process at room temperature was introduced to fabricate large-area growth of Si nanowire (SiNW) arrays. The process was carried out on p-type (100) silicon wafer in aqueous HF+AgNO3 etching solution at room temperature. The wafer surface consisting of SiNW arrays shows the characteristics of low-reflection as low as less than 5% in the 450–790 nm wavelength range. The surface also exhibits super hydrophobicity with a high water contact angle up to 150°. Si wafers with large-area SiNW arrays on the surfaces displaying properties of low-reflection and super-hydrophobicity will have potential applications for fabricating high-efficiency and self-cleaning silicon solar cells. [ABSTRACT FROM PUBLISHER]

Published
2011
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41. An Efficient ML Decoder for Tail-Biting Codes Based on Circular Trap Detection.

Author

Wang, Xiaotao, Qian, Hua, Xiang, Weidong, Xu, Jing, and Huang, Hao

Subjects
*DECODERS (Electronics), *ELECTRONIC data processing, *COMPUTATIONAL complexity, *ALGORITHMS, *MATHEMATICAL optimization
Abstract

Tail-biting codes are efficient coding techniques to eliminate the rate loss in conventional known-tail convolutional codes at a cost of increased complexity in decoders. In addition, tail-biting trellis representation of block codes makes the trellis-based maximum likelihood (ML) decoder desirable for implementation. Circular Viterbi algorithm (CVA) is introduced to decode the tail-biting codes for its decoding efficiency. However, its decoding process suffers from circular traps, which degrade the decoding efficiency. In this paper, we propose an efficient checking rule for the detection of circular traps. Based on this rule, a novel maximum likelihood (ML) decoding algorithm for tail-biting codes is presented. On tail-biting trellis, computational complexity and memory consumption of this decoder are significantly reduced comparing to other available ML decoders, such as the two-phase ML decoder. To further reduce the decoding complexity, we propose a new near-optimal decoding algorithm based on a simplified trap detection strategy. The performance of the above algorithms is validated with simulation. [ABSTRACT FROM AUTHOR]

Published
2013
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