Cloud detectionSocial spider optimizationMulti-objective optimizationCloud detection algorithms have emerged to automate image data analysis because of its prime influential factor in remote sensing image quality. Cloud detection algorithm still needs domain-expert intervention and large number of training ...
Cloud detection in high-resolution satellite images is a critical step for many remote sensing applications, but also a challenge, as such images have limited spectral bands. The contribution of this paper is twofold: We present a dataset called CloudPeru as well as a methodology for cloud ...
Satellite imagesContent based image retrievalQuery by polygonRetrieval refinementcloud detectiongeographic information systemIn last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of ...
Highly accurate nighttime cloud detection in satellite imagery is challenging due to the absence of visible to near-infrared (0.38–3 μm, VNI) data, which is critical for distinguishing clouds from other ground features. Fortunately, Machine learni
title={{"A Cloud Detection Algorithm for Remote Sensing Images Using Fully Convolutional Neural Networks"}}, year={2018}, pages={1-5}, doi={10.1109/MMSP.2018.8547095}, ISSN={2473-3628}, month={Aug}, }展开 文件列表 38-Cloud Segmentation in Satellite Images.zip 38-Cloud Segmentation...
Therefore, finding areas covered with clouds is an important preprocessing step in remote sensing image applications. This paper proposes a cloud detection method for satellite images with high resolution using ground objects' multi-features, such as color, texture, and shape. First, the highly ...
This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a 'pr... M Awrangjeb,M Ravanbakhsh,C Fraser - University of Sussex 被引量: 238发表: 2010年 Satellite detection of cloud liquid water over land...
Cloud Detection is an important pre-processing step for any application involving remote sensing data. This paper presents a deep learning based CloudX-Net architecture, that can detect cloud cover with improved accuracy in comparison to the benchmark from satellite remote sensing images. The proposed...
摘要: Focuses on the evolution of cloud tracking via satellite imagery. Early work on detection of atmospheric motion by remote sensing; Operational satellite detection of winds; Example applications; Research areas.关键词: climate environment global product meteorology ...
This paper presents a method to detect clouds and shadows in Suomi NPP satellite's VIIRS (Visible Infrared Imaging Radiometer Suite) satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the ...