AN ADAPTIVE WATERMARKING ALGORITHM FOR DEM BASED ON DFT Changqng Zhu 1 Zhwe Wang 2 Y Long 1 Chengsong Yang 2 1 Key Laboratory of Vrtual Geographc Envronment, Nanjng Normal Unversty, Nanjng 210054;2 Insttute of Surveyng and Mappng, Informaton Engneerng Unversty, Zhengzhou 450052 Abstract: In ths paper, a dgtal watermarkng algorthm s proposed for DEM data to protect the DEM copyrght. The algorthm s based on the human vsual system (HVS) and the dscrete Fourer transform (DFT). Frstly, the locaton of watermarkng s ascertaned adaptvely accordng on the features of DEM data. Then, the watermark nformaton s embedded to the lowness frequency of the texture regon DFT. Fnally, the DEM data s transformed by DFT and the data wth watermarkng nformaton s obtaned. The experments demonstrate that the proposed algorthm can not only satsfy the watermark transparency, but also have lttle effect on the DEM elevaton, the slope and the contour. In addton, the algorthm s robust to the some nose attacks. Keywords: dgtal elevaton model, dgtal watermark, dscrete Fourer transform, slope, accuracy, adaptve 1 Introducton As an mportant part of the spatal data nfrastructure and Dgtal Earth, dgtal elevaton model (DEM) data s valuable n scence research and applcaton. So how to protect the copyrght and the economc nterests of DEM owners has become an mmnent practcal problem [1~5], and t s n ths context where watermarkng technques come to help us to protect the ownershp rghts The dgtal watermarkng s a new technque of copyrght protecton n recent years, The secret nformaton n the dgtal product s not only mperceptble for the human vsual system, but also s dffcult to remove by the prates [6]. Due to ts outstandng advantages n the protecton of varous types of data, dgtal watermarkng has become an actve and mportant area of research, and manly focuses
on the copyrght protecton of the mage, vdeo, audo and some multmeda nformaton [7~12]. As a new knd of dgtal product, the copyrght of geospatal data protecton has been drawng more and more attenton.and there had been some studes for watermarkng on DEM data. For example, Lu [1] ponted out that the dgtal watermarkng of usual dgtal mages was not sutable for DEM as not alterng the elevaton precson and the results of applcaton to an extent of DEM besdes transparency. In addton to some dgtal watermarkng algorthms were presented to protect DEM based on the dscrete cosne transform (DCT) and the dscrete wavelet transform (DWT). Luo et al. [2] proposed an mproved watermarkng algorthm based on DWT, whch could adaptvely get the watermarkng embeddng strength based on the expanson of wavelet-doman quantzaton nose of the human vson system (HVS). He et al. [3,4,5] proposed a DEM copyrght protecton and camouflage technque based on DEM hstogram, whch can get back the DEM non-destructvely and can realzed the watermark nformaton blnd detecton. These studes promote the DEM copyrght protecton. Nevertheless, t s worth notng that very few of these studes amed at the characterstcs of the DEM data. Compared wth the usual dgtal mages, DEM has ts own character and applcaton value. Besdes the general functons of the usual dgtal mages watermarkng, the DEM watermarkng has some specal demands. In ths paper, an adaptve watermarkng algorthm for the embeddng locaton s brought forward, based on the HVS, the DEM characterstcs and the dscrete Fourer transform (DFT). 2 Algorthm Prncple For DEM, the terran lnes are the mportant feature as collectng more terran nformaton and composng the terran framework [1].Meanwhle, the terran lnes are very senstve for the human vson. If alterng the watermark nformaton on the terran lnes, not only the vson qualty of DEM wll go down, but also the DEM accuracy wll be reduced, and even ts applcaton value wll be lost. Furthermore, the terran lnes wll be dfferent for dfferent DEM. So the embeddng locaton of watermark nformaton wll shft adaptvely wth the dfferent DEM. Hence, the watermarkng algorthm should be more robust embeddng the watermark nformaton nto the terran lnes. 2.1 Selectng the sutable data regon Some studes ndcate that the human vson s more senstve on the flat areas and the edge of the regons compared to other regons.meanwhle, the topographc parameters,
such as slope and aspect, are more senstve for the change of flat areas and edge of the regons than the change of other regons. In order to satsfy the mperceptblty of dgtal watermarkng and the applcaton accuracy of DEM, the watermark nformaton should not be embedded nto these regons. 2.2 Embeddng the watermark nformaton Accordng to the above analyss, Fgure 1 llustrates the flow chart of DEM dgtal watermarkng algorthm based on DFT. Watermark Informaton Scramblng Scrambled Informaton Embeddng Sutable Data Blocks Blockng DFT Watermarked Data Blocks Watermarked DEM Fg.1 Flow chart of embeddng watermarkng (1) Creatng the watermark nformaton: here s a sgnfcatve watermark nformaton, as Fgure 2, whch s a bnary mage. The mage can be recorded as two-valued sequence W = { w}( = 1,2, L, k), where w = ± 1. The watermark nformaton W ' = { w' }( = 1,2, L, k) can be got after scramblng the two-valued sequence. Fg.2 The watermarkng mage (2) Selectng the embeddng locaton: The DEM data s dvded nto N N nonoverlappng data blocks. Therefore, the sutable data blocks can be got by the above method. (3) Embeddng watermark: The scrambled watermark nformaton W ' s embeded to the lowness frequency of the texture regon DFT. The embeddng formula s descrbed as
follows: M ' = { m + α w' }( = 1,2, L, k) ; (4) Generatng watermarked DEM: The watermarked DEM I ' can be got through IDFT. 2.3 Detectng the watermark nformaton The detecton of watermark nformaton s the nverse process of the embeddng watermark nformaton. If possessng the key and the orgnal DEM, the watermark nformaton could be detected. For estmatng the smlarty degree between the detected watermark and the orgnal watermark, the followng formula s adopted: L 1 NC = b, L = 1 ( = 1,2, L, L) (1) Where, b = XNOR( w, w* ), w s the orgnal watermark nformaton, detected watermark nformaton, and L s the length of watermark. w* s the 3 The results and analyss of the experments In order to verfy the proposed algorthm, a DEM s selected as expermental data, where the sze s 512 512 and the grd nterval s 20 m. 3.1 The accuracy analyss of watermarked DEM Table 1 llustratess the basc nformaton of the orgnal DEM and the watermarked DEM, and Table 2 llustratess the statstcal results of elevaton error and slope error of watermarked DEM. Fgure 3 shows the comparson of elevaton of orgnal and watermarked DEM, and Fgure 4 shows the comparson of slope of orgnal and watermarked DEM. Fgure 5 shows the comparson of contour lnes of orgnal and watermarked DEM. Table 1 The basc nformaton of the orgnal DEM and the watermarked DEM Mn. Ele. Max. Ele. Mean Mn. Max. Mean Ele. Slope Slope Slope Orgnal DEM 210 m 1022 m 547 m 0.0 71.14 32.04 Watermarked 210 m 1022 m 547 m 0.0 71.62 32.04
DEM Table 2 The statstcal results of elevaton error and slope error of watermarked DEM Error 0~1 1~2 2~3 3~4 4~5 >5 Max RMSE Ele. Error 84.45% 3.83% 5.91% 5.81% 0.0% 0.0% 3.0 m 0.892 Slope Error 78.40% 8.52% 7.41% 3.90% 1.77% 0.0% 4.99 1.221 Table 1 ndcates that the change of basc nformaton between the orgnal and watermarked DEM s not obvous. Table 2 shows the statstcal results of elevaton error and slope error of watermarked DEM, and the errors are mostly less than 3 unts. Ths ndcates that ths algorthm has obvous advantage at controllng the data accuracy. Fgure 5 shows the change of contour lnes after watermarkng. In the fgure, the contour lnes of watermarked DEM are very close to the orgnal contours. So the watermarked contours can satsfy the applcaton n practce. (a) Orgnal DEM (b) Watermarked DEM (c) The Elevaton Error Fg. 3 The comparson of elevaton of orgnal and watermarked DEM (a) Orgnal Slope (b) Watermarked Slope (c) The Slope Error Fg. 4 The comparson of slope of orgnal and watermarked DEM
3.2 Robustness assessment Fg. 5 The comparson of contours of orgnal and watermarked DEM In ths paper, some nose data s added to the DEM data to study the watermarkng robust. The correlaton coeffcent of detecton result s computed by formula (1). Table 3 llustratess the detecton results. These expermental results ndcate that the proposed algorthm s very robust to the nose. The nose range The detecton result The correlaton coeffcent Table 3 The results of detectng watermarkng [-1,1] [-3,3] [-5,5] 0.998 0.927 0.861 4 Concluson Dgtal watermarkng s a rapd and mportant ssue n dgtal securty, As dgtal watermarkng provdes a potental program for the copyrght protecton of DEM, t s valuable n practce. From what has been addressed n the prevous sectons, we can see that most of exstng dgtal watermarkng algorthms are mostly proposed for the requrements of multmeda data. Nevertheless there are lttle scheme that takes nto account the characterstcs of DEM, therefore, t s not sutable for DEM data. The expermental results demenstrate that the proposed algorthm s not only able to keep
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