  Multispectral images (MSI) contain light information in different wavelengths
of objects, which convey spectral-spatial information and help improve the
performance of various image processing tasks. Numerous techniques have been
created to extend the application of total variation regularization in
restoring multispectral images, for example, based on channel coupling and
adaptive total variation regularization. The primary contribution of this paper
is to propose and develop a new multispectral total variation regularization in
a generalized opponent transformation domain instead of the original
multispectral image domain. Here opponent transformations for multispectral
images are generalized from a well-known opponent transformation for color
images. We will explore the properties of generalized opponent transformation
total variation (GOTTV) regularization and the corresponding optimization
formula for multispectral image restoration. To evaluate the effectiveness of
the new GOTTV method, we provide numerical examples that showcase its superior
performance compared to existing multispectral image total variation methods,
using criteria such as MPSNR and MSSIM.
