Results 31 to 40 of about 90,380 (319)

PACO: Python-Based Atmospheric Correction

Sensors, 2020
The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric ...
Raquel de los Reyes, Maximilian Langheinrich, Peter Schwind, Rudolf Richter, Bringfried Pflug, Martin Bachmann, Rupert Müller, Emiliano Carmona, Viktoria Zekoll, Peter Reinartz   +9 more
doaj   +1 more source

Counting Dense Objects in Remote Sensing Images [PDF]

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Estimating accurate number of interested objects from a given image is a challenging yet important task. Significant efforts have been made to address this problem and achieve great progress, yet counting number of ground objects from remote sensing images is barely studied. In this paper, we are interested in counting dense objects from remote sensing
Guangshuai Gao, Qingjie Liu 0001, Yunhong Wang 0001   +2 more
openaire   +2 more sources

Remote Sensing Upside Down: Exploring the Potential of Ground-Based Multispectral Cameras for Tree Crown Monitoring [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Recent advancements in remote sensing have enabled increasingly detailed analysis of forest canopies using a range of platforms, from satellites to ground-based systems.
M. Goebel, L. Wolf, F. Packwitz, D. Iwaszczuk   +3 more
doaj   +1 more source

Generating Natural Adversarial Remote Sensing Images [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2022
Over the last years, Remote Sensing Images (RSI) analysis have started resorting to using deep neural networks to solve most of the commonly faced problems, such as detection, land cover classification or segmentation. As far as critical decision making can be based upon the results of RSI analysis, it is important to clearly identify and understand ...
Jean-Christophe Burnel, Kilian Fatras, Rémi Flamary, Nicolas Courty   +3 more
openaire   +3 more sources

A review of parallel computing for large-scale remote sensing image mosaicking [PDF]

, 2015
Interest in image mosaicking has been spurred by a wide variety of research and management needs. However, for large-scale applications, remote sensing image mosaicking usually requires significant computational capabilities.
Wei, Jingbo, He, Jijun, Chen, Lajiao, Liu, Peng, Jie, Wei, Ma, Yan   +5 more
core   +1 more source

Remote Sensing Image Haze Removal Based on Superpixel

, 2023
The presence of haze significantly degrades the quality of remote sensing images, resulting in issues such as color distortion, reduced contrast, loss of texture, and blurred image edges, which can ultimately lead to the failure of remote sensing ...
Tiecheng Bai, Yufeng He, Cuili Li
core   +1 more source

Integrating Crowd-sourced Annotations of Tree Crowns using Markov Random Field and Multispectral Information [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Benefiting from advancements in algorithms and computing capabilities, supervised deep learning models offer significant advantages in accurately mapping individual tree canopy cover, which is a fundamental component of forestry management.
Q. Mei, J. Steier, D. Iwaszczuk
doaj   +1 more source

Unsupervised change detection in PolSAR images using siamese encoder–decoder framework based on graph-context attention network

International Journal of Applied Earth Observations and Geoinformation, 2023
Extracting difference features is a key technique for polarimetric synthetic aperture radar (PolSAR) image change detection. Although the current PolSAR change detection algorithms based on convolutional neural networks (CNNs) can capture the local ...
Zhifei Yang, Yan Wu, Ming Li, Xin Hu, Zhikang Li   +4 more
doaj   +1 more source

GROUND FILTERING OF CO-REGISTERED MOBILE AND STATIONARY LASER SCANS BY USING SUPERPOINTS IN RANSAC PLANES [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023
Ground filtering is an important tool for many applications. The high variability of landscapes makes it necessary to perform its computation with 3D points as the only input, that is, with as few as possible algorithm parameters and without any training
D. Stütz, J. Li, J. Li, J. Huai, D. Bulatov   +4 more
doaj   +1 more source

IDENTIFICATION OF MISCLASSIFIED PIXELS IN SEMANTIC SEGMENTATION WITH UNCERTAINTY EVALUATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
Classification, and in particular semantic segmentation, plays a major role in remote sensing. In remote sensing, the classes usually correspond to landcover or landuse types while the data elements are image pixels.
L. E. Budde, D. Bulatov, D. Iwaszczuk
doaj   +1 more source