Results 171 to 180 of about 8,937 (214)

Multiresolution inpainting for reconstruction of missing data in VHR images

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Reconstructing missing data in very high resolution (VHR) multispectral images represents a complex image processing challenge. In this paper, we face this problem through a novel solution based on inpainting. Inpainting is a technique to reconstruct missing regions in a given image by propagating the spectro-geometrical information retrieved from the ...
Lorenzi, Luca, Melgani, Farid, G. Mercier   +2 more
openaire   +2 more sources

Contextual genetic algorithm for compressive sensing reconstruction of VHR images

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013
Reconstructing missing data in very high resolution (VHR) multispectral images represents a complex image processing challenge. In this paper, we propose a new method for the reconstruction of areas obscured by clouds. It is based on compressive sensing (CS) theory, which allows to find sparse signal representations in underdetermined linear equation ...
Lorenzi, Luca, Melgani, Farid, G. Mercier   +2 more
openaire   +1 more source

Sparse Hierarchical Clustering for VHR Image Change Detection

IEEE Geoscience and Remote Sensing Letters, 2015
The traditional clustering approaches are limited for the unsupervised change detection of very high resolution images due to the multimodal distribution of change features. To overcome this difficulty, a sparse hierarchical clustering approach is proposed.
Kun Ding, Chunlei Huo, Yuan Xu, Zisha Zhong, Chunhong Pan   +4 more
openaire   +1 more source

VHR satellite image segmentation based on topological unsupervised learning

2015 14th IAPR International Conference on Machine Vision Applications (MVA), 2015
High spatial resolution satellite imagery has become an important source of information for geospatial applications. Automatic segmentation of high-resolution satellite imagery is useful for obtaining more timely and accurate information. In this paper we introduce a new approach for automatic image segmentation into different regions (corresponding to
Nistor Grozavu, Nicoleta Rogovschi, Guenael Cabanes, Andres Troya-Galvis, Pierre Gancarski   +4 more
openaire   +1 more source

Reclamation Aquaculture Detection Based on VHR UAV Aerial Images

2019 9th International Conference on Information Science and Technology (ICIST), 2019
Unmanned aircraft vehicle (UAV) has emerged widely at the lower cost of obtaining remote sensing imagery, which can collect very high resolution (VHR) data from multispectral or SAR sensor modalities conveniently. This trend facilitates a transition from large scale land-use segmentation to object-level scene understanding.
Jianchao Fan, Xiaoxin Liu, Jianhua Zhao, Xiu Su, Xinxin Wang, Xiang Wang   +5 more
openaire   +1 more source

Change Field: A New Change Measure for VHR Images

IEEE Geoscience and Remote Sensing Letters, 2014
Due to the complexity of very high resolution (VHR) images and the inaccurate correspondence, change feature extraction is the key difficulty of VHR image change detection. In this letter, change field is proposed to represent the complex changes between VHR images.
null Leigang Huo, null Xiangchu Feng, null Chunlei Huo, null Zhixin Zhou, null Chunhong Pan   +4 more
openaire   +1 more source

Building damage scale proposal from VHR satellite image [PDF]

, 2017
Natural hazards have a huge impact in terms of economic losses, affected and killed people. Current exploitation of remote sensed images play a fundamental role in the delineation of damages generated by catastrophic events. Institutions like the United Nations and the European Commission designed services that provide information about the impact of ...
SANDU, CONSTANTIN, GIULIO TONOLO, FABIO, Cotrufo, Silvana, BOCCARDO, PIERO   +3 more
openaire  

Cluster kernels for semisupervised classification of VHR urban images

2009 Joint Urban Remote Sensing Event, 2009
In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples.
Devis Tuia, Gustavo Camps-Valls
openaire   +1 more source

Swarm Optimization of Structuring Elements for VHR Image Classification

IEEE Geoscience and Remote Sensing Letters, 2013
Mathematical morphology has shown to be an effective tool to extract spatial information for remote-sensing image classification. Its application is performed by means of a structuring element (SE), whose shape and size play a fundamental role for appropriately extracting structures in complex regions such as urban areas.
A. Daamouche, Melgani, Farid, N. Alajlan, Conci, Nicola   +3 more
openaire   +1 more source

Use of the second-kind statistics for VHR SAR image retrieval

2012 9th International Conference on Communications (COMM), 2012
The Method of Log Cumulants (MoLC) has been recently proposed for analysis and parameter estimation of the probability density function (pdf) defined in R+. Here the Fourier transform as the characteristics function is replaced with Mellin transform for parameter estimation.
Singh, Jagmal, Datcu, Mihai
openaire   +1 more source