Results 251 to 260 of about 278,436 (276)

Cloud shadow removal from aerial photographs

Pattern Recognition, 1990
Abstract Aerial photographs may contain extremes in brightness variation due to the presence of cloud shadows. The variations will at times be beyond the dynamic range of photographic media, and as a result, either the non-shadowed regions will be severely overexposed or the shadowed regions will be severely underexposed.
Joseph Shou-Pyng Shu, Herbert Freeman
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Cloud-Aware Generative Network: Removing Cloud From Optical Remote Sensing Images

IEEE Geoscience and Remote Sensing Letters, 2020
In the optical remote sensing and earth observation fields, clouds severely obscure the land’s visibility and degrade the image. In recent years, there have been many excellent efforts to mitigate the effects of cloud cover. However, it has been found that there will be some blurs in the area if a single degraded image is restored by autoencoder-based ...
Linjian Sun, Ye Zhang, Xuling Chang, Yanjie Wang, Jiajia Xu   +4 more
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Thin cloud removal with residual symmetrical concatenation network

ISPRS Journal of Photogrammetry and Remote Sensing, 2019
Abstract Thin cloud removal is important for enhancing the utilization of optical remote sensing imagery. Different from thick cloud removal, the pixels contaminated by thin clouds still preserve some surface information. Therefore, thin cloud removal methods usually focus on suppressing the cloud influence instead of replacing the cloudy pixels.
Wenbo Li, Ying Li, Di Chen, Jonathan Cheung-Wai Chan   +3 more
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Removal of Meteoric Iron on Polar Mesospheric Clouds

Science, 2004
Polar mesospheric clouds are thin layers of nanometer-sized ice particles that occur at altitudes between 82 and 87 kilometers in the high-latitude summer mesosphere. These clouds overlap in altitude with the layer of iron (Fe) atoms that is produced by the ablation of meteoroids entering the atmosphere.
John M C, Plane, Benjamin J, Murray, Xinzhao, Chu, Chester S, Gardner   +3 more
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Cloud Detection and Cloud Removal of Satellite Image—A Case Study

2020
The book contributes to the subject area of remote sensing and Geographic Information System. It is focused on the study and analysis of automated cloud detection and removal of satellite imagery using the selection of thresholds value for various spectral tests in the perspective of RSGIS (Ramya, KarthiPrem, Nithyasri in IJIACS 3(2), [1], Rafael ...
Sanju Das, Purnendu Das, Bishwa Ranjan Roy   +2 more
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Automatic cloud and cloud shadow removal method for landsat TM images

IEEE 2011 10th International Conference on Electronic Measurement & Instruments, 2011
Optical Remote Sensing Images are often interfered by clouds and their shadows. In this research, a scheme is proposed to automatically detect and remove clouds and their shadows by integrating complementary information from multitemporal images to generate the cloud-free composite images. Firstly, image classification is used to separate cloud regions
null Gui Zhengke, null Chen Fu, null Yang Jin, null Li Xinpeng, null Li Fangjun, null Zhao Jing   +5 more
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Remote sensing imaging simulation and cloud removal

International Journal of Modern Physics B, 2017
Cloud obstacles obscure ground information frequently during remote sensing imaging which leads to valuable information losses. Removing clouds from a single image becomes challenging since no reference images containing cloud-free regions are available. In order to study cloud removal technologies and evaluate their performances, a method to simulate
Xifang Zhu, Feng Wu, Tao Wu, Chunyu Zhao
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Automatic Cloud Removal from Multitemporal Satellite Images

Journal of the Indian Society of Remote Sensing, 2014
Remote sensing images are more or less influenced by clouds and cloud shadows during the data acquisition, which pose a major challenge in data processing. As a result, many researchers have come up with different methods to detect and remove the clouds and their shadows from remote sensing images. In this paper, an automatic cloud removal algorithm is
S R Surya, Philomina Simon
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Artifact-Free Thin Cloud Removal Using Gans

2019 IEEE International Conference on Image Processing (ICIP), 2019
This paper proposes a framework to train an artifact-free thin cloud removal model using Generative Adversarial Nets (GANs) with thick cloud masks. Satellite images are useful in various applications, however their exploitation is often limited by a presence of clouds.
Toizumi, Takahiro, Zini, Simone, Sagi, Kazutoshi, Kaneko, Eiji, Tsukada, Masato, Schettini, Raimondo   +5 more
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Research on removing cloud from optical images

SPIE Proceedings, 2011
This paper proposes a novel algorithm for distinguishing scenery information from cloud noise in the low-level and high-level detail coefficients using the wavelet decomposition. Also this paper shows approximate coefficients only containing the scenery information, and high-level detail coefficients mainly including the cloud noise and the partial ...
Xifang Zhu, Feng Wu
openaire   +1 more source