The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
Figure 5. work flow of the fusion
3.2 fusion and sharpen
Scattered single points or small targets disturb during
classification even though they usually are comprised with
special target,but in some cases it is not necessary to pay
more attention, So a special designed Vector filter (Ma
Yanhua,etc,2006) is designed to erase odds and ends points,
which is named a vector filter based neighborhood
clustering(NCVF). The filter is used on both kinds of the
images and it makes the fusion easier.
Polynomial registration algorithms were used to as a rough
registration means to get the special relationship of the pixels in
two imaggs, the hyperspectral image are not re-sampled.
Because the two kind images are captured at the same time ,so
the luminance in corresponding bands are high correlation, the
registration between the super pixel and the high special
resolution image pixel can be defined more accurately.
Next step is to get the grads of both image .The hyperspectral
image grads can get vector grade first and then translate it to
scalar quantity, such as ||x||.
Review every hyperspectral image pixel of their grads and the
grade of corresponding high special image area to decide
weather it’s a pure pixel, the criterion can be set according with
the image.
Produce the edge image of the high special resolution image to
segment it as the map to be filled with spectral information or
classifying information, edit it artificially if necessary.
The pure pixel spectral fill to the edge image in their registered
position, and diffusing with a balloon algorithm to cover the
other pixel in the same segments. If there are more than one
spectral in a single segment, the spectral should be calculate
their mean. Spectral will leak out if there are un continuousness
in the edge, so restrict has to set up to avoid spectra’s leaking
out at small holes in the edge. Better image segment algorithms
will be helpful.
The unpure pixel can be get by pixel decomposing. Now that
the pure pixels are filled in the image, the indétermination
during pixel decomposing is reduced. Linear decomposing ruler
is used in this article.
The decomposing can be done step by step with spectra that
already known in neighbor area of the pixel to be
decomposed .First step decompose those composed with two
types of material (super pixels that cover two segments in edge
map) and one of then is known already, Then those composed
with three types of material.Of cause, more step pixel
decomposing is meaningless because of error.
After decomposing, the spectral are filled in the edge map just
as the pure pixel before-mentioned.
3.3 experiments
The method is not well developed yet ,original experiments is
just finished .One experiment images are showed in figure 6,
the hyperspectral image is of 100*40pixel, and RGB image is of
328*235 (the images were acquired before the AMIRS
finished ,so the resolution of the RGB image is lower
relatively).The results is showed in figure 7 and figure 8.
Figure 6. Hyperspectral image and
high spatial resolution image