IEEE Geoscience and Remote Sensing Magazine - June 2021 - 58

SU
Lighting
AB C
Sensor
Lighting
Sensor
Lighting
Sensor
Linear Mixing
Intimate Mixture
One Mixed Pixel
(Tree + Road + Soil)
Endmembers
=+
Wavelength
HSI
Wavelength
(d)
CML
MML
Training
Modality
A
Concentration
Modality
B
Modality
A
Concentration
Modality
B
(e)
FIGURE 3. (continued).
nonconvex problem to an approximate convex model [13].
Another is to break the nonconvex problems down into
several convex subproblems and solve them in parallel by
means of convex ways [14].
In light of the different research goals, the general model
in (2) can be extended to the task-driven variants, covering
a broad scope within the HS RS, including image restoration,
DR, data fusion and enhancement, SU, and CML. It
should be noted that, in the following sections, some representative
methods will be introduced with a focus on nonconvex
modeling, while the alternating direction method
of multipliers (ADMM) optimization framework is recommended
for use as a general solver to solve these nonconvex
models. For specific solutions to these models on each
topic, please refer to the cited references.
58
HS IMAGE RESTORATION
Due to their wealth of spectral information, HS images
have been widely used in different kinds of applications,
including urban planning, agriculture, forestry, target
detection, and so on. However, due to the limitations of
HS imaging systems and weather conditions, HS images
continually suffer from the pollution of various noises.
Figure 4 depicts the different noise types of HS images
observed from airborne and spaceborne sensors. Therefore,
HS image denoising and restoration are necessary
preprocessing steps for subsequent applications to assist
the noise.
The statistical distribution of HS noise is complicated.
For instance, the readout noise, which is assumed to obey
the Gaussian distribution, is produced by the imaging
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE JUNE 2021
Model
Testing
Fused Features
Prediction
Modality
A
or
Modality
B
Fused Features
Projection
Labels
Modality
B
Modality
A
Projection 1
Model
Projection 2
Shared
Features
Testing
Prediction
Shared Features
Prediction
CML
Training
Shared
Features
Labels
Wavelength
Wavelength
Two-Layered Scene
Abundance Maps

IEEE Geoscience and Remote Sensing Magazine - June 2021

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