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Burak Kocuk - IEEE Xplore Author Profile

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Author details

Burak Kocuk

Publications

4

Citations

221

Publications by Year

20162023

Co-Authors:

Santanu S. DeySezen Ece KayacıkXu Andy SunDeniz Tuncer

Burak Kocuk

Affiliation

Faculty of Engineering and Natural Sciences

Sabancı University

Istanbul, Tuzla, Turkey

Publication Topics

Feasible Solution,
Optimal Power Flow,
Second-order Cone Programming,
Semidefinite Programming,
Flow Problem,
Flow Reactor,
Leisure,
Mixed-integer Nonlinear Programming,
Mixed-integer Programming,
New Variables,
Optimization Problem,
Power Flow Equations

Biography

Burak Kocuk received the B.S. degree in industrial engineering and mathematics, the M.S. degree in industrial engineering from Boğaziçi University, Istanbul, Turkey, and the Ph.D. degree in operations research from the School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA. He is currently an Associate Professor with the Industrial Engineering Program, Sabancı University, Istanbul, Turkey. Before joining Sabancı University, he was a Postdoctoral Fellow with the Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA. His research interests include mixed-integer nonlinear programming and stochastic optimization problems, from both theoretical and methodological aspects.(Based on document published on 12 September 2022).

Publications

4

Citations

221

Publications by Year

20162023

Co-Authors:

Santanu S. Dey
Sezen Ece Kayacık
Xu Andy Sun
Deniz Tuncer

Author's Published Works

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Showing 1-25 of 27 results

Journals (18)

Conferences (8)

Early Access Articles (1)

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College of Electronic Science and Technology, National University of Defense Technology (NUDT), Changsha, China(4)
National Airspace Technology Key Laboratory, Beijing, China(3)
School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou, China(2)
IEEE Transactions on Geoscience and Remote Sensing(6)
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Results

Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines

Xinyi Ying;Chao Xiao;Wei An;Ruojing Li;Xu He;Boyang Li;Xu Cao;Zhaoxu Li;Yingqian Wang;Mingyuan Hu;Qingyu Xu;Zaiping Lin;Miao Li;Shilin Zhou;Weidong Sheng;Li Liu

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Early Access Article |

Cited by: Papers (1)

Visible-thermal small object detection (RGBT SOD) is a significant yet challenging task with a wide range of applications, including video surveillance, traffic monitoring, search and rescue. However, existing studies mainly focus on either visible or thermal modality, while RGBT SOD is rarely explored. Although some RGBT datasets have been developed, the insufficient quantity, limited diversity, ...Show More

Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines

Xinyi Ying;Chao Xiao;Wei An;Ruojing Li;Xu He;Boyang Li;Xu Cao;Zhaoxu Li;Yingqian Wang;Mingyuan Hu;Qingyu Xu;Zaiping Lin;Miao Li;Shilin Zhou;Weidong Sheng;Li Liu

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Early Access Article |

Sparsity-Aware Global Channel Pruning for Infrared Small-Target Detection Networks

Shuanglin Wu;Chao Xiao;Yingqian Wang;Jungang Yang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2025 | Volume: 63 | Journal Article |

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For infrared small-target detection, convolutional neural network (CNN)-based methods have demonstrated promising performance. However, due to the small size of the targets, existing infrared small-target detection methods necessitate intricate structures with intensive computation to maintain distinctive features of targets in deep layers, which poses great challenges for deployment on edge devic...Show More

Sparsity-Aware Global Channel Pruning for Infrared Small-Target Detection Networks

Shuanglin Wu;Chao Xiao;Yingqian Wang;Jungang Yang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2025 | Volume: 63 | Journal Article |

Direction-Coded Temporal U-Shape Module for Multiframe Infrared Small Target Detection

Ruojing Li;Wei An;Chao Xiao;Boyang Li;Yingqian Wang;Miao Li;Yulan Guo

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Cited by: Papers (8)

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Infrared small target (IRST) detection aims at separating targets from cluttered background. Although many deep learning-based single-frame IRST (SIRST) detection methods have achieved promising detection performance, they cannot deal with extremely dim targets while suppressing the clutters since the targets are spatially indistinctive. Multiframe IRST (MIRST) detection can well handle this probl...Show More

Direction-Coded Temporal U-Shape Module for Multiframe Infrared Small Target Detection

Ruojing Li;Wei An;Chao Xiao;Boyang Li;Yingqian Wang;Miao Li;Yulan Guo

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos

Chao Xiao;Wei An;Yifan Zhang;Zhuo Su;Miao Li;Weidong Sheng;Matti Pietikäinen;Li Liu

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 12 | Journal Article |

Cited by: Papers (5)

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Moving object detection in satellite videos (SVMOD) is a challenging task due to the extremely dim and small target characteristics. Current learning-based methods extract spatio-temporal information from multi-frame dense representation with labor-intensive manual labels to tackle SVMOD, which needs high annotation costs and contains tremendous computational redundancy due to the severe imbalance...Show More

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos

Chao Xiao;Wei An;Yifan Zhang;Zhuo Su;Miao Li;Weidong Sheng;Matti Pietikäinen;Li Liu

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 12 | Journal Article |

Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos

Qingyu Xu;Longguang Wang;Weidong Sheng;Yingqian Wang;Chao Xiao;Chao Ma;Wei An

IEEE Transactions on Multimedia

Year: 2024 | Volume: 26 | Journal Article |

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Tracking multiple tiny objects is highly challenging due to their weak appearance and limited features. Existing multi-object tracking algorithms generally focus on single-modality scenes, and overlook the complementary characteristics of tiny objects captured by multiple remote sensors. To enhance tracking performance by integrating complementary information from multiple sources, we propose a no...Show More

Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos

Qingyu Xu;Longguang Wang;Weidong Sheng;Yingqian Wang;Chao Xiao;Chao Ma;Wei An

IEEE Transactions on Multimedia

Year: 2024 | Volume: 26 | Journal Article |

DiffDet4SAR: Diffusion-Based Aircraft Target Detection Network for SAR Images

Jie Zhou;Chao Xiao;Bo Peng;Zhen Liu;Li Liu;Yongxiang Liu;Xiang Li

IEEE Geoscience and Remote Sensing Letters

Year: 2024 | Volume: 21 | Journal Article |

Cited by: Papers (12)

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Aircraft target detection in synthetic aperture radar (SAR) images is a challenging task due to the discrete scattering points and severe background clutter interference. Currently, methods with convolution- or transformer-based paradigms cannot adequately address these issues. In this letter, we explore diffusion models for SAR image aircraft target detection for the first time and propose a nove...Show More

DiffDet4SAR: Diffusion-Based Aircraft Target Detection Network for SAR Images

Jie Zhou;Chao Xiao;Bo Peng;Zhen Liu;Li Liu;Yongxiang Liu;Xiang Li

IEEE Geoscience and Remote Sensing Letters

Year: 2024 | Volume: 21 | Journal Article |

RepISD-Net: Learning Efficient Infrared Small-Target Detection Network via Structural Re-Parameterization

Shuanglin Wu;Chao Xiao;Longguang Wang;Yingqian Wang;Jungang Yang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Cited by: Papers (13)

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Infrared small-target detection is a challenging task for deep learning-based methods, because targets tend to disappear in the deep layers. To handle this problem, the existing deep neural networks usually apply various dense and skip connections for feature maintenance. Although these well-designed networks have achieved good detection performance, the complex network structures reduce their eff...Show More

RepISD-Net: Learning Efficient Infrared Small-Target Detection Network via Structural Re-Parameterization

Shuanglin Wu;Chao Xiao;Longguang Wang;Yingqian Wang;Jungang Yang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

You Only Train Once: Learning a General Anomaly Enhancement Network With Random Masks for Hyperspectral Anomaly Detection

Zhaoxu Li;Yingqian Wang;Chao Xiao;Qiang Ling;Zaiping Lin;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Cited by: Papers (18)

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In this article, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). Our method eliminates the need for adjusting parameters or retraining on new test scenes as required by most existing methods. Employing an image-level training paradigm, we achieve a general anomaly enhancement network for hyperspectral AD that only needs to be trained ...Show More

You Only Train Once: Learning a General Anomaly Enhancement Network With Random Masks for Hyperspectral Anomaly Detection

Zhaoxu Li;Yingqian Wang;Chao Xiao;Qiang Ling;Zaiping Lin;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Incorporating Deep Background Prior Into Model-Based Method for Unsupervised Moving Vehicle Detection in Satellite Videos

Chao Xiao;Ting Liu;Xinyi Ying;Yingqian Wang;Miao Li;Li Liu;Wei An;Zhijie Chen

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Cited by: Papers (9)

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Background reconstruction is a key step of moving object detection in satellite videos. Most existing model-based methods exploit low-rank prior to recover background, which has achieved good performance but suffered degradation under complex and dynamic scenes. In this article, we introduce a deep background prior into model-based methods for moving vehicle detection in satellite videos. Our deep...Show More

Incorporating Deep Background Prior Into Model-Based Method for Unsupervised Moving Vehicle Detection in Satellite Videos

Chao Xiao;Ting Liu;Xinyi Ying;Yingqian Wang;Miao Li;Li Liu;Wei An;Zhijie Chen

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection

Tianhao Wu;Boyang Li;Yihang Luo;Yingqian Wang;Chao Xiao;Ting Liu;Jungang Yang;Wei An;Yulan Guo

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Cited by: Papers (55)

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Space-based infrared tiny ship detection aims at separating tiny ships from the images captured by Earth-orbiting satellites. Due to the extremely large image coverage area (e.g., thousands of square kilometers), candidate targets in these images are much smaller, dimer, and more changeable than those targets observed by aerial- and land-based imaging devices. Existing short imaging distance-based...Show More

MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection

Tianhao Wu;Boyang Li;Yihang Luo;Yingqian Wang;Chao Xiao;Ting Liu;Jungang Yang;Wei An;Yulan Guo

IEEE Transactions on Geoscience and Remote Sensing

Year: 2023 | Volume: 61 | Journal Article |

Dense Nested Attention Network for Infrared Small Target Detection

Boyang Li;Chao Xiao;Longguang Wang;Yingqian Wang;Zaiping Lin;Miao Li;Wei An;Yulan Guo

IEEE Transactions on Image Processing

Year: 2023 | Volume: 32 | Journal Article |

Cited by: Papers (287)

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Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds. With the advances of deep learning, CNN-based methods have yielded promising results in generic object detection due to their powerful modeling capability. However, existing CNN-based methods cannot be directly applied to infrared small targets since pooling layers in their networks coul...Show More

Dense Nested Attention Network for Infrared Small Target Detection

Boyang Li;Chao Xiao;Longguang Wang;Yingqian Wang;Zaiping Lin;Miao Li;Wei An;Yulan Guo

IEEE Transactions on Image Processing

Year: 2023 | Volume: 32 | Journal Article |

The First Challenge on Moving Object Detection and Tracking in Satellite Videos: Methods and Results

Yulan Guo;Qian Yin;Qingyong Hu;Feng Zhang;Chao Xiao;Ye Zhang;Hanyun Wang;Chenguang Dai;Jian Yang;Zhuang Zhou;Weilong Guo;Xiyu Qi;Kelong Tu;Cong Xu;Shudan Zhu;Lai Chen;Bin Lin;Chaocan Xue;Jinlei Zheng;Limei Qin;Ying Li;Manqi Zhao;Lu Ruan;Mingpeng Cui;Guanchen Ding;Guangwei Jiang;Zhenzhong Chen;Yuhan Sun;Kaiyang Cao;Lingyu Kong;Shaodong Chen;Zhicheng Zhao;Qin Shen;Lei Liu;Chenglong Li;Yun Xiao

2022 26th International Conference on Pattern Recognition (ICPR)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

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In this paper, we briefly summarize the first challenge on moving object detection and tracking in satellite videos (SatVideoDT). This challenge has three tracks related to satellite video analysis, including moving object detection (Track 1), single object tracking (Track 2), and multiple-object tracking (Track 3). 123, 89, and 70 participants successfully registered, while 37, 42, and 29 teams s...Show More

The First Challenge on Moving Object Detection and Tracking in Satellite Videos: Methods and Results

Yulan Guo;Qian Yin;Qingyong Hu;Feng Zhang;Chao Xiao;Ye Zhang;Hanyun Wang;Chenguang Dai;Jian Yang;Zhuang Zhou;Weilong Guo;Xiyu Qi;Kelong Tu;Cong Xu;Shudan Zhu;Lai Chen;Bin Lin;Chaocan Xue;Jinlei Zheng;Limei Qin;Ying Li;Manqi Zhao;Lu Ruan;Mingpeng Cui;Guanchen Ding;Guangwei Jiang;Zhenzhong Chen;Yuhan Sun;Kaiyang Cao;Lingyu Kong;Shaodong Chen;Zhicheng Zhao;Qin Shen;Lei Liu;Chenglong Li;Yun Xiao

2022 26th International Conference on Pattern Recognition (ICPR)

Year: 2022 | Conference Paper |

Video Infrared Small Target Detection Combining Hybrid Attention with Cross-Scale Feature Fusion

Zaiping Lin;Yihang Luo;Qiang Ling;Tianhao Wu;Chao Xiao;Boyang Li

2022 2nd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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Infrared small target detection is widely used in marine resource utilization, high-precision navigation, ecological environment monitoring, and other fields. Traditional detection methods rely on manual feature templates and prior knowledge, which are not robust in complex scenarios. Although achieving promising results, existing deep learning-based methods mainly focus on single-frame target det...Show More

Video Infrared Small Target Detection Combining Hybrid Attention with Cross-Scale Feature Fusion

Zaiping Lin;Yihang Luo;Qiang Ling;Tianhao Wu;Chao Xiao;Boyang Li

2022 2nd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT)

Year: 2022 | Conference Paper |

RSMOT: Remote Sensing Multi-Object Tracking Network with Local Motion Prior for Objects in Satellite Videos

Chao Xiao;Shuanglin Wu;Yingqian Wang;Miao Li;Wei An;Zhijie Chen

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Year: 2022 | Conference Paper |

Cited by: Papers (3)

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Multi-object tracking (MOT) in satellite videos is a new and challenging task. The difficulties stem from the extremely small objects and the low contrast between objects and background. To tackle the challenges of MOT in satellite videos, a multi-object tracking method is proposed in this paper to incorporate the local motion prior into the network. Specifically, we design a local cost volume con...Show More

RSMOT: Remote Sensing Multi-Object Tracking Network with Local Motion Prior for Objects in Satellite Videos

Chao Xiao;Shuanglin Wu;Yingqian Wang;Miao Li;Wei An;Zhijie Chen

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Year: 2022 | Conference Paper |

Nonconvex Tensor Low-Rank Approximation for Infrared Small Target Detection

Ting Liu;Jungang Yang;Boyang Li;Chao Xiao;Yang Sun;Yingqian Wang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2022 | Volume: 60 | Journal Article |

Cited by: Papers (49)

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Infrared small target detection is an important fundamental task in the infrared system. Therefore, many infrared small target detection methods have been proposed, in which the low-rank model has been used as a powerful tool. However, most low-rank-based methods assign the same weights for different singular values, which will lead to inaccurate background estimation. Considering that different s...Show More

Nonconvex Tensor Low-Rank Approximation for Infrared Small Target Detection

Ting Liu;Jungang Yang;Boyang Li;Chao Xiao;Yang Sun;Yingqian Wang;Wei An

IEEE Transactions on Geoscience and Remote Sensing

Year: 2022 | Volume: 60 | Journal Article |

DSFNet: Dynamic and Static Fusion Network for Moving Object Detection in Satellite Videos

Chao Xiao;Qian Yin;Xinyi Ying;Ruojing Li;Shuanglin Wu;Miao Li;Li Liu;Wei An;Zhijie Chen

IEEE Geoscience and Remote Sensing Letters

Year: 2022 | Volume: 19 | Journal Article |

Cited by: Papers (39)

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Moving object detection (MOD) in satellite videos remains challenging due to the extremely small size of the interested targets and the highly complex background. Both the intra-frame (static) and inter-frame (dynamic) information are of great importance to MOD. In this letter, we propose a two-stream detection network named dynamic and static fusion network (DSFNet) to tackle the MOD problem in s...Show More

DSFNet: Dynamic and Static Fusion Network for Moving Object Detection in Satellite Videos

Chao Xiao;Qian Yin;Xinyi Ying;Ruojing Li;Shuanglin Wu;Miao Li;Li Liu;Wei An;Zhijie Chen

IEEE Geoscience and Remote Sensing Letters

Year: 2022 | Volume: 19 | Journal Article |

Dense Dual-Attention Network for Light Field Image Super-Resolution

Yu Mo;Yingqian Wang;Chao Xiao;Jungang Yang;Wei An

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2022 | Volume: 32, Issue: 7 | Journal Article |

Cited by: Papers (26)

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Light field (LF) images can be used to improve the performance of image super-resolution (SR) because both angular and spatial information is available. It is challenging to incorporate distinctive information from different views for LF image SR. Moreover, the long-term information from the previous layers can be weakened as the depth of network increases. In this paper, we propose a dense dual-a...Show More

Dense Dual-Attention Network for Light Field Image Super-Resolution

Yu Mo;Yingqian Wang;Chao Xiao;Jungang Yang;Wei An

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2022 | Volume: 32, Issue: 7 | Journal Article |

Baseline-Adaptive Light Field Depth Estimation Based on Stereo Matching

Yu Mo;Chao Xiao;Jungang Yang;Wei An

2021 6th International Symposium on Computer and Information Processing Technology (ISCIPT)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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Using the spatial and angular information contained in a light field, the depth map can be generated and the structure of the scene can be inferred. However, it is always challenging to obtain an accurate and robust depth map in different scenes with different resolutions and baselines. In this paper, we propose a resolution and baseline adaptive light field depth estimation method to increase the...Show More

Baseline-Adaptive Light Field Depth Estimation Based on Stereo Matching

Yu Mo;Chao Xiao;Jungang Yang;Wei An

2021 6th International Symposium on Computer and Information Processing Technology (ISCIPT)

Year: 2021 | Conference Paper |

Camera Array Calibration Using a Simple Checkerboard Pattern

Jungang Yang;Chao Xiao;Pu Wang;Yougan Luo;Chengjin An

2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)

Year: 2019 | Conference Paper |

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Traditional camera calibration method usually considers a single camera or dual cameras. As the growing development of imaging technology, multi camera and camera array are used in more and more applications. In this paper, a calibration method for camera array is proposed. The intrinsic and extrinsic parameters for an individual camera are obtained using single camera calibration method. Then the...Show More

Camera Array Calibration Using a Simple Checkerboard Pattern

Jungang Yang;Chao Xiao;Pu Wang;Yougan Luo;Chengjin An

2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)

Year: 2019 | Conference Paper |

Toward Real-World Light Field Depth Estimation: A Noise-Aware Paradigm Using Multi-Stereo Disparity Integration

Yu Mo;Jungang Yang;Chao Xiao;Wei An

Year: 2019 | Volume: 7 | Journal Article |

Cited by: Papers (2)

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Producing depth maps of a scene is essential in many light field applications. Numerous algorithms have been developed to obtain an accurate depth map on public datasets. However, real-world light field images obtained by cameras have noises produced by hardware limitations. Existing methods do not perform well on noisy scenes. In this paper, we propose a noise-aware light field depth estimation a...Show More

Toward Real-World Light Field Depth Estimation: A Noise-Aware Paradigm Using Multi-Stereo Disparity Integration

Yu Mo;Jungang Yang;Chao Xiao;Wei An

Year: 2019 | Volume: 7 | Journal Article |

Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution

Yingqian Wang;Jungang Yang;Yulan Guo;Chao Xiao;Wei An

IEEE Signal Processing Letters

Year: 2019 | Volume: 26, Issue: 1 | Journal Article |

Cited by: Papers (94)

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Camera arrays provide spatial and angular information within a single snapshot. With refocusing methods, focal planes can be altered after exposure. In this letter, we propose a light field refocusing method to improve the imaging quality of camera arrays. In our method, the disparity is first estimated. Then, the unfocused region (bokeh) is rendered by using a depth-based anisotropic filter. Fina...Show More

Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution

Yingqian Wang;Jungang Yang;Yulan Guo;Chao Xiao;Wei An

IEEE Signal Processing Letters

Year: 2019 | Volume: 26, Issue: 1 | Journal Article |

Notice of Removal: Flexible Refocusing Method for Camera Arrays Based on Reprojection

Chao Xiao;Jungang Yang;Yingqian Wang;Wei An

2018 International Computers, Signals and Systems Conference (ICOMSSC)

Year: 2018 | Conference Paper |

Removed.Show More

Notice of Removal: Flexible Refocusing Method for Camera Arrays Based on Reprojection

Chao Xiao;Jungang Yang;Yingqian Wang;Wei An

2018 International Computers, Signals and Systems Conference (ICOMSSC)

Year: 2018 | Conference Paper |

Disparity Estimation for Camera Arrays Using Reliability Guided Disparity Propagation

Yingqian Wang;Jungang Yang;Yu Mo;Chao Xiao;Wei An

Year: 2018 | Volume: 6 | Journal Article |

Cited by: Papers (17)

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Light field cameras become increasingly popular recently, as they can capture 3-D geometry of the scene in a single snap-shot. Many post-capture adjustments can be realized after the disparity map or the equivalent depth map being estimated. Recent studies about light field depth recovery are more designed for commercial microlens cameras, such as Lytro and Raytrix. However, camera arrays capture ...Show More

Disparity Estimation for Camera Arrays Using Reliability Guided Disparity Propagation

Yingqian Wang;Jungang Yang;Yu Mo;Chao Xiao;Wei An

Year: 2018 | Volume: 6 | Journal Article |

Fast Convergence Strategy for Multi-Image Superresolution via Adaptive Line Search

Yingqian Wang;Jungang Yang;Chao Xiao;Wei An

Year: 2018 | Volume: 6 | Journal Article |

Cited by: Papers (10)

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Multi-image superresolution (SR) techniques produce a high-resolution image from several low-resolution observations. Previous reconstruction-based SR approaches focus more on the optimization models but have not adequately emphasized the mathematic-solving techniques for this typically ill-conditioned and under-determined large scale problem. Since step size plays an important role in the iterati...Show More

Fast Convergence Strategy for Multi-Image Superresolution via Adaptive Line Search

Yingqian Wang;Jungang Yang;Chao Xiao;Wei An

Year: 2018 | Volume: 6 | Journal Article |

Flexible Refocusing Method for Camera Arrays Based on Reprojection

Chao Xiao;Yingqian Wang;Jungang Yang;Wei An

2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC)

Year: 2017 | Conference Paper |

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Light field provides enough information so that one can post-process images after acquisition. A representative application of light-field is refocusing, which changes the infocus region of images. In this paper, a flexible algorithm of refocusing is proposed for images captured by camera arrays. By utilizing the parameters estimated by camera calibration, the reprojection can be used to produce i...Show More

Flexible Refocusing Method for Camera Arrays Based on Reprojection

Chao Xiao;Yingqian Wang;Jungang Yang;Wei An

2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC)

Year: 2017 | Conference Paper |

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