
Hyperspectral Image Super-Resolution Meets Deep Learning: A Survey and Perspective
Xinya Wang, Qian Hu, Yingsong Cheng and Jiayi Ma
IEEE/CAA Journal of Automatica Sinica 2023
[paper]
Computer Vision for Intelligence Perception and Sustainability
I am currently a Ph.D. student in Electronic Information School, Wuhan University, China, supervised by Prof. Jiayi Ma in the lab of Multi-spectral Vision Processing (MVP). I am also supervised by Prof. Junjun Jiang in the School of Computer Science and Technology, Harbin Institute of Technology, China. Before that, I obtained the BEng. degree from the Wuhan University.
My research focuses on processing multi-dimensional data and developing novel algorithms for high-resolution image enhancement and restoration. My work has been applied to several real-world applications, including blind super-resolution, hyperspectral sharpening, light field super-resolution and infrared image enhancement.
Currently, I am seeking a Postdoctoral position to continue advancing my research and applying my skills and expertise to new challenges. You can find my full CV here.
Ph.D. in Signal and Information Processing 2018 - present
Wuhan University, Wuhan, China
B.Eng. in Communication Engineering 2014 - 2018
Wuhan University, Wuhan, China
For a full list of publications please see my CV or Google Scholar.
Hyperspectral Image Super-Resolution Meets Deep Learning: A Survey and Perspective
Xinya Wang, Qian Hu, Yingsong Cheng and Jiayi Ma
IEEE/CAA Journal of Automatica Sinica 2023
[paper]
A Group-Based Embedding Learning and Integration Network for Hyperspectral Image Super-Resolution
Xinya Wang, Qian Hu, Junjun Jiang and Jiayi Ma
IEEE Transactions on Geoscience and Remote Sensing 2022
[paper]
Group Shuffle and Spectral-Spatial Fusion for
Hyperspectral Image Super-Resolution
Xinya Wang, Yingsong Cheng, Xiaoguang Mei, Junjun Jiang and Jiayi Ma
IEEE Transactions on Computational Imaging 2022
[paper]
Learning an Epipolar Shift Compensation for Light Field Image Super-Resolution
Xinya Wang, Jiayi Ma, Peng Yi, Xin Tian, Junjun Jiang and Xiaoping Zhang
Information Fusion 2022
[paper]
Hyperspectral Image Super-Resolution via Recurrent Feedback Embedding and Spatial–Spectral Consistency Regularization
Xinya Wang, Jiayi Ma and Junjun Jiang
IEEE Transactions on Geoscience and Remote Sensing 2022
[paper]
Contrastive Learning for Blind Super-Resolution via a Distortion-Specific Network
Xinya Wang, Jiayi Ma and Junjun Jiang
IEEE/CAA Journal of Automatica Sinica 2022
[paper]
Dilated Projection Correction Network based on Autoencoder for Hyperspectral Image Super-Resolution Neural Networks
Xinya Wang, Jiayi Ma, Junjun Jiang and Xiaoping Zhang
Neural Networks 2021
[paper]
DRF: Disentangled Representation for Visible and Infrared Image Fusion
Han Xu, Xinya Wang and Jiayi Ma
IEEE Transactions on Instrumentation and Measurement 2021
[paper]
Infrared imaging, generally, of low quality, plays an important role
in security surveillance and target detection, which hinders the progress of large-scale AI-based studies and a range of applications. To this end, an infrared light field imaging
enhancement system is built for the first time, including a infrared light field imaging device, a large-scale infrared light field dataset (IRLF-WHU), and a progressive fusion network for infrared image enhancement (IR-PFNet).
[Paper] [Code] [Dataset]
Acquiring and processing hyperspectral data can be time-consuming and expensive, which causes a series of issues involving data scarcity, class skew and target background restriction. To this end, we tend to raise a new paradigm of HSI generation, generating a vast amount of HSI with a rich diversity in various categories and scenes, closely resembling realistic data.
[Project]
Natural Science Introductory Course (Undergraduate course, TA, 2022 Fall)