You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Proceedings, XXth congress

An Adaptive Content-Based Localized Watermarking
for Remote Sensing Image
Xianmin Wang " Zequn Guan*
Chenhan Wu*
? College of Remote Sensing Information Engineering, Wuhan University! No.129 Luoyu Road,
Wuhan City, Hubei Province, P.R.China, 430079
KEY WORDS: Vision, Application, Algorithms, Feature,
Image, Spot
In this paper, we proposed a new adaptive content-based localized watermarking algorithm for remote sensing images based on DWT,
which adaptively embeds corresponding watermarks into the local regions of the remote sensing image instead of the entire one. In
order to improve watermarking capability against attacks in the frequency area, we selected some stable feature points in the remote
sensing image, then used them to identify the locations where we inserted the local watermarks, namely we embedded the watermarks
into the local sub-images centered by those feature points. When the remote sensing image is cropped , we can also detect and orient
watermarks by the feature points in the remaining one. Moreover the algorithm took the new watermarking-embedding strategy based
on DWT domain to embed the local watermarks, namely watermarks should be embedded into the low frequency space firstly, and the
remains are embedded into the high frequency spaces according to their significance. And different embedding strength for
watermarks should be applied to the low frequency space and the high ones respectively. In order to further improve robustness of
watermarks, the embedded local watermark is designed to be orthogonal to the feature vector of the low frequency space (LL3) in
DWT area of the corresponding sub-image, which means that watermarking casting is remote sensing image content dependent. In
addition, the algorithm exploited the Neymann-Pearson criterion to detect watermarks. Experimental results show that the
watermarking algorithm is robust to all kinds of attacks, especially cropping.
1. Introduction
The demand for remote sensing data has increased dramatically
mainly due to the large number of applications capable to
exploit remotely sensed data and images. Along with the
popularization of Internet and the development of multimedia
techniques, people can embezzle remote sensing images
lawlessly through the Internet. But by embedding watermarks
into remote sensing image, we can effectually prevent such
problems as copyright violation, illegal copying, easily forging
and so on.
Recently watermarking technique has developed very rapidly,
but there is still a large distance from practical application and a
lot of practical problems not resolved (Wentong CAI, 2001a;
Hong Heather, 2000a; Hyung-Woo Lee, 2001a). There have
been many watermarking algorithms, most of which can be
classified into spacial algorithms (Hua Xiansheng, 2001a; Yi
Kaixiang, 2001a) and frequency algorithms (He Renya, 2001a;
Kutter M., 1999b; Christine I, 1997b; Podilchuk C I, 1998a; Xia
X, 1997b; Pei Wang, 2002a). Generally speaking, spacial
algorithms have poorer robustness against compressing, noise
adding and filtering, and as for frequency algorithms, it would
be very hard to resist cropping attack if we embed watermarks
into the frequency area of the whole image, because now we
have only part of image, and can't get the size of the original
remote sensing image and the position of the cropping image in
the original remote sensing image, then it's difficult to ensure
the position of watermarks embedding.
In addition, in order to ensure the robustness of watermarking
algorithms, we think watermarks should be embedded into the
most remarkable weight of remote sensing image. So
watermarks should be bound together with the feature collection
of the image, and namely, the coefficient collection
chosen to accommodate watermarks can generally be seen as the
feature vector collection of a remote sensing image (Cox I J,
1997b). At present, in most of watermarking algorithms the
choice of watermarks has nothing to do with the image content,
which in fact is quite disadvantageous to robustness and security
of an algorithm, because when the remote sensing image with
watermarks suffers from intentional (for instance malignantly
destroying or watermarks deleting) or unconscious attacks (for
example remote sensing image compression, filter, scan, copy,
noise pollution and size change), if the embedded watermarks is
not related to the image content, attackers would easily remove
watermarks in the case of not destroying the basic quality of the
remote sensing image.
Given the above two reasons, in this paper we proposed an
adaptive content-based localized watermarking algorithm for
remote sensing images. The algorithm utilized the relatively
stable feature points in the remote sensing image to mark the
position to embed watermarks, then independently and
adaptively embedded watermarks into that local area
corresponding with each feature point, so when there is only
part of the image, we can also orient and detect watermarks
without the participation of the original remote sensing image.
Therefore this algorithm can effectively resist cropping (In this
paper, cropping refers to detecting watermarks in the remaining
image after cropping, and the size of the original image and the
position of the remaining image in the original image are
unknown). In addition, the algorithm binds the watermarks
together with the feature of the corresponding sub-image,
namely the algorithm is remote sensing image content-based, so
when the watermarks are destroyed, the features of the remote
sensing image is also destroyed, then the remote sensing image
would count for nothing.
And in section 2 of the paper, we presented the adaptive