Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

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Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: An Adaptive Content-Based Localized Watermarking Algorithm for Remote Sensing Image Xianmin Wang, Zequn Guan, Chenhan Wu

Document type:: Multivolume work

Structure type:: Chapter

An Adaptive Content-Based Localized Watermarking Algorithm 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 wangmin10291(@sina.com KEY WORDS: Vision, Application, Algorithms, Feature, ABSTRACT: zequne@public.wh.hb.en wuchenhan(@etang.com 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 192 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

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