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Mapping without the sun
Zhang, Jixian

(a) ETM+Multispectral Image, (b) Panchromatic Image,
(c) Fused Image Based on PCA, (d) Fused Image Based on 2DPCA
Figure 1. Results of Image Fusion Experiment
4.2 Analysis
From images shown in Figure 1, some useful points can be
drawn as follows.
(1) In the fused image based on PCA-based technique, although
the spatial resolution is greatly improved, the spectral
information is badly lost. Furthermore, it is difficult to
distinguish the surface features form each other.
(2) Compared with the multispectral images, the spatial
resolution is improved and the spectral information is well
preserved in the fused image based on 2DPCA.
(3) Compared with c), fused image in d) has better spatial
resolution and enhanced spectral information; meanwhile, it is
easy to distinguish the surface features. Therefore,
2DPCA-based algorithm has better performance than
PCA-based algorithm.
Why the performance of 2DPCA-based method is apparently
better than that of PCA-based one? We consider that there are
two main reasons.
(1) In PCA-based algorithm, an image must be transformed
into a 1-D vector when PCA is applied to the image and can not
utilize its structural information. In 2DPCA-based algorithm,
however, 2DPCA is directly applied to the image matrices
instead of ID vector. Therefore, the structural information of
the image is effectively utilized.
(2) In PCA-based algorithm, the multispetral images are
regarded as a whole, i.e., each band of the multispetral images
is regarded as a feature, in the analysis and reconstruction
processes, but the case in 2DPCA-based algorithm is
oppositional, i.e., each band of the multispetral images is
regarded as many features whose number is equal to the height
of the image.
5. Conclusions
In this paper, 2DPCA is introduced into image fusion in remote
sensing, and a novel image fusion algorithm based on 2DPCA
is proposed. 2DPCA-based technique has some advantages, in
contrast to PCA-based method.
(1) 2DPCA is directly applied on image matrices, and the
images are regarded as 2D matrices in reconstruction instead of