Results 181 to 190 of about 223,998 (212)

Classification of Hyperspectral and Lidar with Deep Rotation Forest

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
In this work, a novel deep rotation forest is proposed to fuse hyperspectral (HS) and LiDAR. First, we extract the spatial and elevation information of two datasets by using morphological filters. Then, each feature source is applied to superpixel segmentation and then are treated as the input of deep rotation forest.
Junshi Xia, Zuheng Ming
openaire   +2 more sources

Fusion of hyperspectral and LiDAR data for forest attributes estimation

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
In this paper a system for the fusion of hyperspectral and airborne laser scanning (ALS) data for the estimation of forest attributes is presented. In particular we focused on the classification of tree species, the estimation of stem diameter at breast height (DBH) and the estimation of the stem volume.
Dalponte, Michele, Frizzera, Lorenzo, Gianelle, Damiano   +2 more
openaire   +2 more sources

Monitoring radioactive contamination by hyperspectral lidar

SPIE Proceedings, 2015
There are already significant amounts of hazardous radioactive substances in the world. It, potentially, leads to a major damage and contamination of large areas. Laser sensing can serve as a highly effective method of searching and monitoring of radioactive contamination.
A. S. Grishkanich, V. G. Bespalov, S. K. Vasiev, A. S. Gusarov, S. V. Kascheev, V. V. Elizarov, A. P. Zhevlakov   +6 more
openaire   +1 more source

Inelastic hyperspectral Scheimpflug lidar for microalgae classification and quantification

Applied Optics, 2021
An inelastic hyperspectral Scheimpflug lidar system was developed for microalgae classification and quantification. The correction for the refraction at the air–glass–water interface was established, making our system suitable for aquatic environments.
Xiang Chen, Yiming Jiang, Quankai Yao, Jiali Ji, Julian Evans, Sailing He   +5 more
openaire   +2 more sources

LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing
The fusion of hyperspectral and light detection and range (LiDAR) data has been an active research topic. Existing fusion methods have ignored the high-dimensionality and redundancy challenges in hyperspectral images (HSIs), despite that band selection ...
Alan Wee-chung Liew, Judy Yang
exaly   +3 more sources

Deep fusion of hyperspectral and LiDAR data for thematic classification

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Recently, the fusion of hyperspectral and light detection and ranging (LiDAR) data has obtained a great attention in the remote sensing community. In this paper, we propose a new feature fusion framework using deep neural network (DNN). The proposed framework employs a novel 3D convolutional neural network (CNN) to extract the spectral-spatial features
Yushi Chen, Chunyang Li, Pedram Ghamisi, Chunyu Shi, Yanfeng Gu   +4 more
openaire   +1 more source

Fusion of hyperspectral and LiDAR data in classification of urban areas

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
In this paper, the fusion of hyperspectral and Li-DAR data is taken into account in order to develop a new classification framework for the accurate analysis of urban areas. In this method, an attribute profile is considered in order to model the spatial information of LiDAR and hyper-spectral data. In parallel, in order to reduce the redundancy of the
Pedram Ghamisi, Jón Atli Benediktsson, Stuart R. Phinn   +2 more
openaire   +4 more sources

Intrinsic Scene Properties From Hyperspectral Images and LiDAR

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019
In this paper, a novel reflectance model is proposed to recover intrinsic images from remote sensing hyperspectral images (HSIs). Intrinsic image recovery is a well-known challenging and underconstrained problem in computer vision and it becomes even more severely ill posed for HSIs.
Xudong Jin, Yanfeng Gu
openaire   +1 more source

Fusion of Hyperspectral and LiDAR Data With a Novel Ensemble Classifier

IEEE Geoscience and Remote Sensing Letters, 2018
Due to the development of sensors and data acquisition technology, the fusion of features from multiple sensors is a very hot topic. In this letter, the use of morphological features to fuse a hyperspectral (HS) image and a light detection and ranging (LiDAR)-derived digital surface model (DSM) is exploited via an ensemble classifier. In each iteration,
Junshi Xia, Naoto Yokoya, Akira Iwasaki
openaire   +2 more sources

Hyperspectral tree species classification with an aid of lidar data

2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2014
Classification of tree species is one of the most important applications in remote sensing. A methodology to classify tree species using hyperspectral and LiDAR data is proposed. The data processing consists of shadow correction, individual tree crown delineation, classification by support vector machine (SVM) and postprocessing by a smoothing filter ...
Tomohiro Matsuki, Naoto Yokoya, Akira Iwasaki   +2 more
openaire   +2 more sources