Results 71 to 80 of about 30,598 (209)

Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery [PDF]

, 2008
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive ...
Chang, Chein-I, Tourneret, J.Y., Dobigeon, Nicolas, Tourneret, Jean-Yves, Chang, C.I., Dobigeon, N.   +5 more
core   +1 more source

Hyperspectral imaging for food applications [PDF]

2015 23rd European Signal Processing Conference (EUSIPCO), 2015
Food quality analysis is a key area where reliable, nondestructive and accurate measures are required. Hyperspectral imaging is a technology which meets all of these requirements but only if appropriate signal processing techniques are implemented. In this paper, a discussion of some of these state-of-the-art processing techniques is followed by an ...
Marshall, Stephen, Kelman, Timothy, Qiao, Tong, Murray, Paul, Zabalza, Jaime   +4 more
openaire   +2 more sources

Hyperspectral colon tissue cell classification [PDF]

, 2004
A novel algorithm to discriminate between normal and malignant tissue cells of the human colon is presented. The microscopic level images of human colon tissue cells were acquired using hyperspectral imaging technology at contiguous wavelength intervals ...
Rajpoot, Nasir M. (Nasir Mahmood), Turner, Martin J., Rajpoot, Kashif   +2 more
core  

Overview of Hyperspectral Image Classification

Journal of Sensors, 2020
With the development of remote sensing technology, the application of hyperspectral images is becoming more and more widespread. The accurate classification of ground features through hyperspectral images is an important research content and has attracted widespread attention. Many methods have achieved good classification results in the classification
Wenjing Lv, Xiaofei Wang 0010
openaire   +1 more source

Illumination invariance and shadow compensation via spectro-polarimetry technique [PDF]

, 2013
A major problem for obtaining target reflectance via hyperspectral imaging systems is the presence of illumination and shadow effects. These factors are common artefacts, especially when dealing with a hyperspectral imaging system that has sensors in the
Jackman, James, Soori, Umair, Hong, Kan, Ibrahim, Izzati, Richardson, Mark A., Yuen, Peter W. T., Chen, Tong   +6 more
core   +1 more source

Hyperspectral images segmentation: a proposal

, 2009
Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous
GORETTA, Nathalie, CHRISTOPHE, Florio, LELONG, Camille, Fiorio, Christophe, ROGER, Jean-Michel, Gorretta, Nathalie, Bellon Maurel, Véronique, RABATEL, Gilles, BELLON-MAUREL, Véronique   +8 more
core  

Singular spectrum analysis for effective feature extraction in hyperspectral imaging

, 2014
As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise ...
Zabalza, Jaime, Wang, Zheng, Ren, Jinchang, Marshall, Stephen, Wang, Jun   +4 more
core   +1 more source

An End-to-End Framework for the Classification of Hyperspectral Images in the Wood Domain

IEEE Access
Hyperspectral images consist of a multitude of spectral bands for each pixel. Spectral bands provide information about wavelengths that may cover a larger spectrum of what the human eye may see.
Roberto Confalonieri, Phyu Phyu Htun, Boyuan Sun, Tammam Tillo   +3 more
doaj   +1 more source

Wavelet based segmentation of hyperspectral colon tissue imagery [PDF]

, 2003
Segmentation is an early stage for the automated classification of tissue cells between normal and malignant types. We present an algorithm for unsupervised segmentation of images of hyperspectral human colon tissue cells into their constituent parts by ...
Rajpoot, Nasir M. (Nasir Mahmood), Rajpoot, Kashif   +1 more
core   +1 more source

Small Sample Classification of Hyperspectral Remote Sensing Images Based on Sequential Joint Deeping Learning Model

IEEE Access, 2020
Although hyperspectral remote sensing images have rich spectral features, for small samples of remote sensing images, feature selection, feature mining, and feature integration are very important.
Zesong Wang, Cui Zou, Weiwei Cai
doaj   +1 more source