Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Liaoying Zhao"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 18987-19002 (2024)
In recent years, tensor representation-based approaches have been widely studied in hyperspectral anomaly detection. However, these methods still suffer from two key issues. First, the various complex regularizations imposed on the background compone
Externí odkaz:
https://doaj.org/article/8a580092959943b3ba22338478229b32
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 4885-4896 (2022)
Due to the powerful reconstruction ability, deep learning based hyperspectral anomaly detection methods have been prevalent in recent years. However, the capability of neural networks and the meaning of latent space remains unexplainable to some exte
Externí odkaz:
https://doaj.org/article/51f216ab77ca4dcea1967c09d9a3c407
Publikováno v:
IEEE Access, Vol 10, Pp 2140-2153 (2022)
Latent low-rank representation has been applied to multi-level image decomposition for the fusion of infrared and visible images to obtain good results. However, when the original infrared and visible images are of low quality, the visual effect of t
Externí odkaz:
https://doaj.org/article/db9a6e3444fc4378b7cd3a7f603687cf
Publikováno v:
Remote Sensing, Vol 15, Iss 15, p 3890 (2023)
Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by v
Externí odkaz:
https://doaj.org/article/f837a4825cfe40f495425bee8202f813
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 5807-5822 (2020)
The traditional graph Laplacian model has been widely used in many computer vision tasks. The small target detection technique is one of the most challenging computer vision tasks in various practical applications. This article presents a small targe
Externí odkaz:
https://doaj.org/article/eafc3c744a724869abaed11b9d63f902
Publikováno v:
IEEE Access, Vol 7, Pp 180027-180038 (2019)
The reliability of feature matching is required for accurate remote sensing image registration. Outliers reduce the accuracy and effectiveness of feature matching. This paper proposes a novel feature matching method that utilizes the global geometric
Externí odkaz:
https://doaj.org/article/5a12aa16b572476e83c02170497d05d2
Publikováno v:
Remote Sensing, Vol 14, Iss 3, p 441 (2022)
In recent years, neural network-based anomaly detection methods have attracted considerable attention in the hyperspectral remote sensing domain due to their powerful reconstruction ability compared with traditional methods. However, actual probabili
Externí odkaz:
https://doaj.org/article/cd49943d1e92408ea83a1025ae2c39bd
Publikováno v:
Remote Sensing, Vol 13, Iss 18, p 3602 (2021)
Hyperspectral band selection (BS) is an effective means to avoid the Hughes phenomenon and heavy computational burden in hyperspectral image processing. However, most of the existing BS methods fail to fully consider the interaction between spectral
Externí odkaz:
https://doaj.org/article/f7c8fd9452f64acfad2fc2f10269d368
Publikováno v:
Remote Sensing, Vol 13, Iss 16, p 3313 (2021)
Shallow underwater topography has important practical applications in fisheries, navigation, and pipeline laying. Traditional multibeam bathymetry is limited by the high cost of largescale topographic surveys in large, shallow sand wave areas. Remote
Externí odkaz:
https://doaj.org/article/4f4935537e534200a01269bf28eafddd
Publikováno v:
Remote Sensing, Vol 13, Iss 16, p 3147 (2021)
Convolution-based autoencoder networks have yielded promising performances in exploiting spatial–contextual signatures for spectral unmixing. However, the extracted spectral and spatial features of some networks are aggregated, which makes it diffi
Externí odkaz:
https://doaj.org/article/fd111c62a5c949ec88e93b44e0aca235