Zobrazeno 1 - 10
of 29
pro vyhledávání: '"mine image"'
Publikováno v:
Meitan xuebao, Vol 49, Iss 9, Pp 4038-4050 (2024)
In the complex confined space of underground coal mine, some environmental factors such as uneven illumination of artificial light source, heavy concentration of dust and fog in the working face, and complex electromagnetic interference can seriously
Externí odkaz:
https://doaj.org/article/e0850da657464a598687640bb80462b5
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 4, Pp 63-68 (2024)
The existing mine image denoising algorithms have limited effectiveness in removing complex noise, and their processing speed cannot meet the requirements of real-time monitoring. In order to solve the above problems, a mine image denoising algorithm
Externí odkaz:
https://doaj.org/article/403226fa8672488486aa2b4294f01c69
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 3, Pp 56-64 (2024)
There is a phenomenon of low lighting and excessive dust in underground mines, which leads to uneven lighting, blurriness, and loss of details in the images captured by monitoring videos. It affects subsequent intelligent image recognition. Existing
Externí odkaz:
https://doaj.org/article/14e597a5f022484f9fb2549c0a561de6
A line feature matching algorithm for mine images based on line segment detection and LT descriptors
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 2, Pp 72-82 (2024)
Image matching is an extremely important part of simultaneous localization and mapping (SLAM) technology. It is used to determine camera position and posture based on the transformation relationship between images. The image matching method based on
Externí odkaz:
https://doaj.org/article/47286e132b714c0897302e64507babd4
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 5, Pp 74-81 (2023)
The visual simultaneous localization and mapping (SLAM) algorithm based on the feature point method has certain applications in coal mines. However, due to factors such as uneven lighting, variable lighting, and alternating light and dark areas, the
Externí odkaz:
https://doaj.org/article/03c26ef5d7ac4f4db1c82e9b05217b4b
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 11, Pp 76-83, 120 (2023)
Due to the impact of high dust and low illumination in underground environments, mine images have problems such as low resolution and blurry details. When existing image super-resolution reconstruction algorithms are applied to mine images, it is dif
Externí odkaz:
https://doaj.org/article/97528f54989144d789a305721b4788ac
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2846 (2024)
A novel zero-reference low-light image-enhancement approach based on noise estimation (ZLEN) is proposed to mitigate noise interference in image-enhancement processes, while the tenets of zero-reference and lightweight network architecture are mainta
Externí odkaz:
https://doaj.org/article/5932c9294fe34225bf10f4a94d473d2b
Publikováno v:
Gong-kuang zidonghua, Vol 48, Iss 8, Pp 43-49 (2022)
The uneven distribution of light sources and weak light in coal mines lead to low brightness and unclear image. The traditional Retinex algorithm has the problems of detail loss, edge blur and halo when processing low illumination images of coal mine
Externí odkaz:
https://doaj.org/article/b726beb50310481987fb6a454ecd97d5
Akademický článek
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Publikováno v:
Gong-kuang zidonghua, Vol 46, Iss 9, Pp 74-78 (2020)
Aiming at problem that dictionary learning method was poorly effective in reconstruction of mine image with noise and complex environment, a super-resolution reconstruction method of mine image based on online multi-dictionary learning was proposed.
Externí odkaz:
https://doaj.org/article/57530686e12f4a4ab940af975860912c