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Mapping without the sun
Zhang, Jixian

which could automatically vary the integrating windows in
according with the features in the sub-image, is presented to
detect whether the noise dot or the target. The maximum
window is 9x9.
4) The wavelet coefficient of the optical image can be regarded
as the fusion value when the wavelet coefficient of the SAR
image may be noise dot. Otherwise, the fusion value is
calculated using equation (4) in the window which the noise
dot is detected.
5) Reconstructing the SAR image using lifting wavelet
The scheme is followed as:
Figure. 1 The scheme of the image fusion
Fig. 2(a) is a Radarsat SAR original image. Fig. 2(b) is a TM
original image. The intention of the image fusion is to integrate
the information of the TM image to SAR image. The
Daubechies9/7 wavelet is used to decompose the images with
the lifting means, and level is 3. The first SAR sub-image is
handled with regional average method. Then the SAR and
optical sun-images are integrated with the power average, and
the powers are respectively 0.6 and 0.4. When integrating the
high-frequency sub-images, the ratio method of the variances is
used after the noise dots have detected along the horizontal
direction and vertical direction using the ratio method of the
energy. The experiments could be present Fig.2(c):
The intention in the paper is that the fusion image can be used
to extract the features well in order to match the real-time
image (real aperture radar image) and refer image (fusion
image). As a result, we respectively extract the features using
the SAR original image and the fusion image [8] . Fig.3 shows
that the fusion image could detect the targets well.
Fig. 3(a) and (b) are the results of the SAR image and the
fusion image using the LOG features extraction. Fig. 3(c) and
(d) are the results of the SAR image and the fusion image using
the FACET features extraction. A mass of the noise dots have
been retained in the Fig. 3(b) and (d), and the continuity of the
features is more obvious in the Fig. 3(d). The experiment
proves that the fusion image is better than the original SAR
image for feature extraction.
(b) TM image
Figure.2 The original image and fusion image
(a) SAR image
(c) Fusion image