Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Cailan Gong"'
Publikováno v:
Remote Sensing, Vol 16, Iss 21, p 4030 (2024)
The robust detection of infrared small targets plays an important role in infrared early warning systems. However, the high-brightness interference present in the background makes it challenging. To solve this problem, we propose a weighted improved
Externí odkaz:
https://doaj.org/article/ebad5d0b362e46e49d71d8794f2a51a5
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3367 (2024)
Accurate on-orbit wavelength calibration of the spaceborne hyperspectral payload is the key to the quantitative analysis and application of observational data. Due to the high spectral resolution of general spaceborne hyperspectral greenhouse gas (GH
Externí odkaz:
https://doaj.org/article/ab0f011fd743400b9ef4f50818aac431
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1614 (2024)
Airborne sensing images harness the combined advantages of hyperspectral and high spatial resolution, offering precise monitoring methods for local-scale water quality parameters in small water bodies. This study employs airborne hyperspectral remote
Externí odkaz:
https://doaj.org/article/9f8dc9ca8ffc4d7c95b8a2b4b4acc98d
Publikováno v:
IEEE Access, Vol 10, Pp 68731-68739 (2022)
Haze may affect the quality of optical remote sensing images, thus limiting the scope of their application. Remote sensing image dehazing has become important in remote sensing image preprocessing, promoting the use of remote sensing data and the pre
Externí odkaz:
https://doaj.org/article/29cbc94bd56847c891f0624fff5e7e3b
Publikováno v:
Remote Sensing, Vol 15, Iss 21, p 5221 (2023)
The extensive existence of high-brightness ice and snow underlying surfaces in polar regions presents notable complexities for cloud detection in remote sensing imagery. To elevate the accuracy of cloud detection in polar regions, a novel polar cloud
Externí odkaz:
https://doaj.org/article/63d23ae0037048938c9730cba6c63c18
Publikováno v:
Remote Sensing, Vol 15, Iss 20, p 5001 (2023)
According to current research, machine learning algorithms have been proven to be effective in detecting both optical and non-optical parameters of water quality. The use of satellite remote sensing is a valuable method for monitoring long-term chang
Externí odkaz:
https://doaj.org/article/a4ce025911b649acab10e197a4cd75ae
Publikováno v:
Remote Sensing, Vol 15, Iss 17, p 4333 (2023)
Lakes play a crucial role in the earth’s ecosystems and human activities. While turbidity is not a direct biochemical indicator of lake water quality, it is relatively easy to measure and indicates trophic status and lake health. Although ocean col
Externí odkaz:
https://doaj.org/article/3e60dd5782c64373be070794dede2d6c
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 5029 (2022)
Non-optically active water quality parameters in water bodies are important evaluation indicators in monitoring urban water quality. Over the past years, satellite remote sensing techniques have increasingly been used to assess different types of sub
Externí odkaz:
https://doaj.org/article/8822a0ba3b7641ceb64c3a2b17d5f85f
Publikováno v:
Applied Sciences, Vol 12, Iss 20, p 10523 (2022)
The non-uniform haze distribution in remote sensing images, together with the complexity of the ground information, brings many difficulties to the dehazing of remote sensing images. In this paper, we propose a multi-input convolutional neural networ
Externí odkaz:
https://doaj.org/article/fe692e48fb8d43ab9e1f437b8e935b2b
Publikováno v:
Earth and Space: From Infrared to Terahertz (ESIT 2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b2b8ee0d28eed69487f92b54b865fe5
https://doi.org/10.1117/12.2664935
https://doi.org/10.1117/12.2664935