Results 231 to 240 of about 4,953 (252)

Hyperspectral band selection based on graph clustering

2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), 2012
In this paper we present a new method for hyperspectral band selection problem. The principle is to create a band adjacency graph (BAG) where the nodes represent the bands and the edges represent the similarity weights between the bands. The Markov Clustering Process (abbreviated MCL process) defines a sequence of stochastic matrices by alternation of ...
Rachid Hedjam, Mohamed Cheriet
openaire   +2 more sources

Best bands selection for detection in hyperspectral processing

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
We explore the role of best bands algorithms in the context of maximizing the performance of hyperspectral algorithms. Specifically, we first focus on creating an intuitive framework for how metrics quantify the distance between two spectra. Focusing on the spectral angle mapper (SAM) metric, we demonstrate how the separability of two spectra can be ...
openaire   +1 more source

Optimal Neighboring Reconstruction for Hyperspectral Band Selection

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Band selection, as an effective and popular dimensional reduction methods for hyperspectral image (HSI), has raised wide attention in recent years. In this paper, we propose a novel band selection method called optimal neighboring reconstruction (ONR). Compared to conventional methods, ONR mainly has following advantages.
Fahong Zhang 0003, Qi Wang 0009, Xuelong Li 0001   +2 more
openaire   +1 more source

Band Selection for Hyperspectral Imagery with PCA-MIG

2012
Although hyperspectral imagery provides abundant information about bands, their high dimensionality also substantially increases the computational burden. An interesting task in hyperspectral data processing is to reduce the redundancy of the spectral and spatial information without loss of any valuable details.
Kitti Koonsanit, Chuleerat Jaruskulchai, Apisit Eiumnoh   +2 more
openaire   +2 more sources

Reducing the Computational Load of Hyperspectral Band Selection Using the One-Bit Transform of Hyperspectral Bands

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
This paper concentrates on reducing the computational complexity of hyperspectral image band selection algorithms via one-bit transform which can be obtained using simple filtering and comparison operations. Firstly, one-bit transform of each band is obtained and noisy and less-discriminative bands, which are decided according to the total number of ...
Demir, Begum, Ertürk, Sarp
openaire   +1 more source

Compact hyperspectral imager with selectable bands

SPIE Proceedings, 2006
This paper gives an overview of the configuration and design of a Compact Hyper spectral imager with feature of having selectable bands in the visible and near infrared spectral region of 0.4 to 0.9?m. The instrument is configured for spatial resolution of 500m and swath of 128Km from 700Km polar orbit with a 12-bit quantization.
A. Roy Chowdhury, K. R. Murali
openaire   +1 more source

Hyperspectral band selection via region-aware latent features fusion based clustering

Information Fusion, 2022
Xinwang Liu, Chang Tang, Zhenglai Li
exaly  

Hyperspectral Band Selection With Iterative Graph Autoencoder

IEEE Transactions on Geoscience and Remote Sensing, 2023
Yuan Zhou 0006, Qingren Yao, Shuwei Huo, Xiaofeng Li 0001   +3 more
openaire   +2 more sources

Graph regularized spatial–spectral subspace clustering for hyperspectral band selection

Neural Networks, 2022
Xinwang Liu, Chang Tang, En Zhu
exaly  

A Fast Neighborhood Grouping Method for Hyperspectral Band Selection

IEEE Transactions on Geoscience and Remote Sensing, 2021
Xuelong Li, Qiang Li, Qi Wang
exaly