Abstract
Multispectral images contain many clues of surface
characteristics of the objects, thus can be used in many
computer vision tasks, e.g., recolorization and segmentation. However, due to the complex geometry structure of
natural scenes, the spectra curves of the same surface can
look very different under different illuminations and from
different angles. In this paper, a new Multispectral Image
Intrinsic Decomposition model (MIID) is presented to decompose the shading and reflectance from a single multispectral image. We extend the Retinex model, which is
proposed for RGB image intrinsic decomposition, for multispectral domain. Based on this, a subspace constraint
is introduced to both the shading and reflectance spectral
space to reduce the ill-posedness of the problem and make
the problem solvable. A dataset of 22 scenes is given with
the ground truth of shadings and reflectance to facilitate
objective evaluations. The experiments demonstrate the effectiveness of the proposed method