Search Results - "Shen, Huanfeng"

A MAP-Based Algorithm for Destriping and Inpainting of Remotely Sensed Images by Huanfeng Shen, Huanfeng Shen, Liangpei Zhang, Liangpei Zhang

“…Remotely sensed images often suffer from the common problems of stripe noise and random dead pixels. The techniques to recover a good image from the…”
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Total-Variation-Regularized Low-Rank Matrix Factorization for Hyperspectral Image Restoration by He, Wei, Zhang, Hongyan, Zhang, Liangpei, Shen, Huanfeng

“…In this paper, we present a spatial spectral hyperspectral image (HSI) mixed-noise removal method named total variation (TV)-regularized low-rank matrix…”
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Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network by Wei, Yancong, Yuan, Qiangqiang, Shen, Huanfeng, Zhang, Liangpei

“…In the field of multispectral (MS) and panchromatic image fusion (pansharpening), the impressive effectiveness of deep neural networks has recently been…”
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Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network by Yuan, Qiangqiang, Zhang, Qiang, Li, Jie, Shen, Huanfeng, Zhang, Liangpei

“…Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the performance of the subsequent HSI interpretation and applications. In…”
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An Integrated Framework for the Spatio-Temporal-Spectral Fusion of Remote Sensing Images by Shen, Huanfeng, Meng, Xiangchao, Zhang, Liangpei

“…Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and spectral resolutions. In this paper, we propose an integrated framework…”
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Hyperspectral Image Restoration Using Low-Rank Matrix Recovery by Zhang, Hongyan, He, Wei, Zhang, Liangpei, Shen, Huanfeng, Yuan, Qiangqiang

“…Hyperspectral images (HSIs) are often degraded by a mixture of various kinds of noise in the acquisition process, which can include Gaussian noise, impulse…”
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Hyperspectral Image Denoising Employing a Spectral-Spatial Adaptive Total Variation Model by Yuan, Qiangqiang, Zhang, Liangpei, Shen, Huanfeng

“…The amount of noise included in a hyperspectral image limits its application and has a negative impact on hyperspectral image classification, unmixing, target…”
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Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges by Meng, Xiangchao, Shen, Huanfeng, Li, Huifang, Zhang, Liangpei, Fu, Randi

“…•This paper provided a holistic review of the pansharpening methods.•The methods were evaluated from a new perspective based on meta-analysis.•The CS-based…”
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Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China by Shen, Huanfeng, Huang, Liwen, Zhang, Liangpei, Wu, Penghai, Zeng, Chao

“…The trade-off between the temporal and spatial resolutions, and/or the influence of cloud cover, makes it difficult to obtain continuous fine-scale satellite…”
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Hyperspectral Image Denoising Using Local Low-Rank Matrix Recovery and Global Spatial–Spectral Total Variation by He, Wei, Zhang, Hongyan, Shen, Huanfeng, Zhang, Liangpei

“…Hyperspectral images (HSIs) are usually contaminated by various kinds of noise, such as stripes, deadlines, impulse noise, Gaussian noise, and so on, which…”
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Robust registration for remote sensing images by combining and localizing feature- and area-based methods by Feng, Ruitao, Du, Qingyun, Li, Xinghua, Shen, Huanfeng

“…Highly accurate registration is one of the essential requirements for numerous applications of remote sensing images. Toward this end, we have developed a…”
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Recovering missing pixels for Landsat ETM+ SLC-off imagery using multi-temporal regression analysis and a regularization method by Zeng, Chao, Shen, Huanfeng, Zhang, Liangpei

“…Since the scan line corrector (SLC) of the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor failed permanently in 2003, about 22% of the pixels in an…”
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Hyperspectral Image Denoising via Noise-Adjusted Iterative Low-Rank Matrix Approximation by He, Wei, Zhang, Hongyan, Zhang, Liangpei, Shen, Huanfeng

“…Due to the low-dimensional property of clean hyperspectral images (HSIs), many low-rank-based methods have been proposed to denoise HSIs. However, in an HSI,…”
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The Relationships between PM2.5 and Meteorological Factors in China: Seasonal and Regional Variations by Yang, Qianqian, Yuan, Qiangqiang, Li, Tongwen, Shen, Huanfeng, Zhang, Liangpei

“…The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the…”
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Noise Removal From Hyperspectral Image With Joint Spectral-Spatial Distributed Sparse Representation by Li, Jie, Yuan, Qiangqiang, Shen, Huanfeng, Zhang, Liangpei

“…Hyperspectral image (HSI) denoising is a crucial preprocessing task that is used to improve the quality of images for object detection, classification, and…”
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A Spatial and Temporal Nonlocal Filter-Based Data Fusion Method by Cheng, Qing, Liu, Huiqing, Shen, Huanfeng, Wu, Penghai, Zhang, Liangpei

“…The tradeoff in remote sensing instruments that balances the spatial resolution and temporal frequency limits our capacity to monitor spatial and temporal…”
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A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution by Shen, Huanfeng, Zhang, Liangpei, Huang, Bo, Li, Pingxiang

“…Super resolution image reconstruction allows the recovery of a high-resolution (HR) image from several low-resolution images that are noisy, blurred, and down…”
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Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems by Shen, Huanfeng, Zhang, Liangpei

“…Building the physics-driven mechanism model has always been the core scientific paradigm for parameter estimation in Earth surface systems, and developing the…”
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Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning by Zhang, Qiang, Yuan, Qiangqiang, Li, Jie, Li, Zhiwei, Shen, Huanfeng, Zhang, Liangpei

“…Thick cloud and its shadow severely reduce the data usability of optical satellite remote sensing data. Although many approaches have been presented for cloud…”
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Estimating surface soil moisture from satellite observations using a generalized regression neural network trained on sparse ground-based measurements in the continental U.S by Yuan, Qiangqiang, Xu, Hongzhang, Li, Tongwen, Shen, Huanfeng, Zhang, Liangpei

“…[Display omitted] •The scale mismatch issue is accounted for using extended triple collocation.•Generalized regression neural network obtains a good…”
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