Open AccessShadow modelling and correction techniques in hyperspectral imaging
Author(s) -
Roper T.,
Andrews M.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2012.4406
Subject(s) - hyperspectral imaging , endmember , shadow (psychology) , shading , artificial intelligence , projection (relational algebra) , computer vision , computer science , image (mathematics) , compensation (psychology) , simplex , mathematics , algorithm , computer graphics (images) , psychology , geometry , psychoanalysis , psychotherapist
Shadowing and illumination variations, caused by scene topography or non‐uniform lighting, are present in virtually all image data. Given its prevalence and nuisance value when making quantitative image measurements, the development of accurate shading compensation techniques is essential. The linear mixture model of image formation is broadly employed when dealing with hyperspectral data but makes no explicit provision for shading and this can lead to inaccurate analysis results. In this reported work, the effect of shading on a hyperspectral image is demonstrated, and new methods for mitigating the effect using a forced‐zero endmember and conical sub‐simplex projection are presented. It is shown that together they provide the most accurate and theoretically sound shadow‐corrected data.