Hyperspectral fluorescence imaging (HSFI) is potentially useful for assessing food and
agricultural products, because it combines the merits of both hyperspectral imaging and …

该文提出了一种以高光谱图像分析为目标的基于独立成分分析的高光谱图像降维和压缩方法.
该方法首先通过独立成分分析提取高光谱数据的光谱特征实现高光谱图像降维 …

In this paper, we present a summary of our ongoing research on the classification of
hyperspectral images. We are experimenting with both supervised and unsupervised …

A spectral angle based feature extraction method, Spectral Clustering Independent
Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue …

Conventional remote sensing classification algorithms assume that the data in each class
can be modelled using a multivariate Gaussian distribution. As this assumption is often not …

Conventional remote sensing classification techniques that model the data in each class
with a multivariate Gaussian distribution are inefficient, as this assumption is generally not …

Advances in hyperspectral images have dramatically boosted remote sensing applications
by providing abundant information using hundreds of contiguous spectral bands. However …

Automatic detection of early rottenness caused by P enicillium is still a challenge due to the
high similarity between the rotten region and sound tissue, and the large variations in …

This paper investigates the effect of spectral screening on processing hyperspectral data
through Independent Component Analysis (ICA). ICA is a multivariate data analysis method …

This paper investigates the efficiency of spectral metrics when used in spectral screening of
hyperspectral imagery. Spectral screening is the technique of selecting from the data a …