English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In order to understand the characteristics of the data collected by hyperspectral imaging systems, it is important to discuss the physics behind the scene radiance field incident on the imaging system. A dominant effect in hyperspectral remote sensing is the mixing of radiant energies contributed from different materials present in a given pixel. The basic assumption of mixture modelling is that within a given scene, the surface is covered by a small number of distinct materials that have relatively constant spectral properties. It is most common to assume that the radiance reflected by different materials in a pixel can spectrally combine in a linear additive manner to produce the pixel radiance/reflectance, even when that might not be the case e.g. where the mixing process leads to nonlinear combinations of the radiance and where the linear assumption fails to hold. This can occur where there is significant relative three-dimensional structure within a given pixel. Without detailed knowledge of the dimensional structure, it can be very difficult to correctly ‘‘un-mix’’ the contributions of the various materials. This work aims to evaluate the correctness of the linear assumption in the mixture modelling using some laboratory measurements. Study was conducted using some sheets made of cellulose materials of different colours in 400-800 nm spectral range. Experimental results have shown that a correction term must be applied to the gains and offsets in the linear model. The obtained results can be extended to satellite sensors that acquire images in the above mentioned spectral range

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

VALIDITY ASSESSMENT OF PIXEL LINEAR SPECTRAL MIXING THROUGH LABORATORY MEASUREMENTS