Colour Spaces Effects on Improved Discrete Wavelet

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Published in IET Signal Processing

Received on 5th December 2012

Revised on 21st February 2013

Accepted on 24th February 2013

doi: 10.1049/iet-spr.2012.0380

ISSN 1751-9675

Colour spaces effects on improved discrete wavelettransform-based digital image watermarkingusing Arnold transform mapMehdi Khalili, David Asatryan

Institute for Informatics and Automation Problems, National Academy of Science, Yerevan, Armenia

E-mail: [email protected]

Abstract:The most digital image watermarking algorithms have nearly always been realised in red, green and blue (RGB) colourspace. In this study, a secure, robust and imperceptible CDMA image watermarking scheme which uses discrete wavelettransform is proposed and tested in eight colour spaces RGB, YCbCr, JPEG-YCbCr, YIQ, YUV, hue, saturation, intensity,hue, saturation, value and CIELab to determine which colour space is more effective in watermarking algorithms based oncorrelation techniques and provides a result which does not differ immeasurably from the original with respect toimperceptibility and robustness. In the proposed scheme, a scrambled binary image by Arnold transform map, afterencryption, is embedded into sub-images of the rst channel wavelet decomposition of intended colour space using block

processing technique. The experimental results show that the proposed approach provides extra imperceptibility, security androbustness against JPEG compression and different noise attacks compared to the similar proposed methods in earlier works.

1 IntroductionAlong with the rapid development of multimedia technologies,

protecting the copyright of digital media has become animportant topic because of digital media can be copied andmodied easily. Therefore data hiding techniques have beenwidely used in multimedia security applications such ascopyright protection, authentication and transaction tracking.Many schemes have been proposed to full the designrequirements of various kinds of applications. As an effectivescheme, digital watermarking technique has received muchattention in the past decades [1,2].

To function as an effective tool to enforce ownership rights,the watermarking scheme must meet the requirements of good

imperceptibility, strong robustness and high-level security.Particularly, owing to the property of imperceptibility, digitalwatermarking takes an advantage in application overtraditional steganography and cryptography for the purposeof copyrights protection: the watermarked multimedia can beused in an overt manner, despite the presence of watermarks.Accordingly, much effort has been devoted to thedevelopment of reliable methods for perceptual qualityassessment in watermarking [3].

Watermark can be embedded onto the signal in spatialdomain or frequency domain. In frequency domain signal istransformed by using transforms such as discrete cosinetransform (DCT), discrete Fourier transform (DFT), discrete

wavelet transform (DWT) and the watermark is embeddedonto the coefcients obtained in frequency domain [4].Among transform domains, watermarking in DWT domainhas drawn extensive attention for its good time-frequency

features and its accurate matching of the human visualsystem (HVS) [5]. In addition, watermarking algorithms havebeen named according to embedded multimedia contentssuch as image, audio and video. For example: Chen et al. in[6, 7] proposed two DWT-based audio watermarkingalgorithms that one of them is based on optimisation schemeusing group-amplitude quantisation and the other embedsinformation by energy-proportion scheme. So that, by usingnormalised energy instead of probability, the study rewritesthe entropy in information theory as energy proportionfunction. Preda et al. in [810] proposed three DWT-basedvideo watermarking approaches in which the watermarksused are binary images. Although, in one of them aspread-spectrum technique is used to spread the power

spectrum of the watermark data, in the two others,watermarking methods are based on a combination of spreadspectrum and quantisation. Also, in [11], Deng and Jiang

proposed a DWT-based image watermarking algorithm inwhich the code-division multiple access (CDMA) encoded

binary watermark, adaptively is embedded into the third leveldetail sub-band of DWT domain.

On the other hand, colour spaces abound, but not all ofthem are appropriate for the entire spectrum of image

processing tasks. A colour space is a mean of specifyingcolours, and they can be classied into three basic parts:HVS-based colour spaces [e.g. red, green and blue (RGB),HVS, hue, saturation, intensity (HSI) and etc.], application

speci

c (e.g. YCbCr, YUV, YIQ and etc.) and CIE colourspaces (e.g. CIELab and etc.) [12]. Within rst category,the most widely used colour space in digital imagewatermarking is RGB (short for Red-Green-Blue), a

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device-dependent colour space loosely based on the HVSphotoreceptors. The main problem with processing in thisdomain is that RGB is psychologically non-intuitive, and is

perceptually non-uniform [12]. Another other problemoccurs when algorithms are applied to RGB images.As there is no separation between colour and intensityinformation, changes that are made to the image arenon-hue preserving. Phenomenal colour spaces also form

part of this rst category incorporating colour spaces suchas hue, saturation, value (HSV) and HSI, which are simplylinear transformations from the RGB space. As such theysuffer from lack of information about chromaticity, anddeciencies associated with their relationship to human

perception [12]. The second category deals withapplication-based colour spaces. This includes CMY(Cyan-Magenta-Yellow) used in printing applications andTV-related colour spaces such national television systemcommittee (NTSCs) YIQ, YUV and YCbCr [12]. The thirdcategory deals with the CIE colour spaces. InternationalCommission on Illumination (CIE) species three colourspaces: CIE*XYZ, CIE*Lab and CIE*Luv, which CIE*Laband CIE*Luv provide a perceptually equal space [12].

In this paper a CDMA digital images watermarkingfor ownership verication and image authenticationapplications, is proposed and tested in RGB, HSV, HSI,YCbCr, JPEG-YCbCr, YIQ, YUV and CIELab colourspaces to explore how the choice of colour space, inuencesthe results of correlation based image watermarkingalgorithms with respect to changes in watermarkinganticipating properties such as imperceptibility androbustness against different attacks. In the proposedscheme, for more security, before watermark embedding

process, the binary watermark image after scrambling byArnold transform map (ATM) method is reshaped to asequence and then a random binary sequence R of size n is

adopted to encrypt the watermark, where n is the size of thewatermark. This adopting process uses a pseudo-randomnumber generator to determine the pixel to be used on agiven key. On the other hand, the RGB channels of thehost image are converted to the intended channels and thenthe rst channel is pre-ltered to enhance embedding

process. After that, low frequency sub-band of waveletdecomposition of its rst channel, is quantised and dividedto different sub-blocks with the certain sub-block size toembed the encrypted watermark.

2 Discrete wavelet transform

The wavelet transform describes a multi-resolutiondecomposition process in terms of expansion of an imageonto a set of wavelet basis functions. Discrete wavelettransformation has its own excellent space frequencylocalisation property [13]. Application of DWT intwo-dimensional (2D) images corresponds to 2D lterimage processing in each dimension. The input image isdivided into four non-overlapping multi-resolutionsub-bands by the lters, namely LL1 (approximationcoefcients), LH1 (vertical details), HL1 (horizontal details)and HH1 (diagonal details). The sub-band (LL1) is

processed further to obtain the next coarser scale of waveletcoefcients, until some nal scale N is reached. When N

is reached, 3N+ 1 sub-band are obtained consisting of themulti-resolution sub-bands. Which are LLX and LHX, HLXand HHX where X ranges from 1 until N. Generally,most of the image energy is stored in the LLX sub-bands [13].

3 Colour spaces

As it was mentioned above, a colour space is a mathematicalrepresentation of a set of colours. Three fundamental colourmodels are: colour spaces based on HVS (e.g. RGB, HVS,HSI and etc.); application specic (e.g. YCbCr,JPEG-YCbCr, YUV, YIQ and etc.) and CIE colour spaces(e.g. CIELab and etc.). The RGB colour space is widely

used in computer graphics and imaging. Red, green, andblue are three primary additive colours which the individualcomponents are added together to form a desired colour andare represented by a 3D, Cartesian coordinate system.However, RGB is not very efcient when dealing withreal-world images [14]. YCbCr is a component colourspace used by digital video. Unlike the RGB model, YCbCr

breaks the visual information into black and white (luma)signal and two colour components. It separates luminancefrom chrominance (lightness from colour). With many morerods than cones, the human eye is more attuned to

brightness and less to colour differences. Hence the YCbCrcolour system allows more attention to be paid to Y, andless to Cb and Cr [15]. To improve the obtained resultsfrom YCbCr colour space a new test with the same method,original images and watermark image is performed onanother rescaling of YCbCr called JPEG-YCbCr which isused in the JPEG image format, with Y, Cb and Cr in [0,1].The transform from RGB to JPEG-YCbCr and the

backward transform from JPEG-YCbCr to RGB are shownin our previous work in [16]. The YIQ system is the colour

primary system adopted by NTSC for colour televisionbroadcasting. Like RGB, the YIQ colour space is adevice-dependent colour space which means the actualcolour you see on your monitor depends on what kind ofmonitor you are using and what its settings are. In thiscolour space, Y-component stands for luminance or

brightness, the I-component seems to mimic mostly shiftsfrom blue, through purple, to red colours (with increasing

I), and the Q-component seems to mimic mostly the valueof green; the I and Q components jointly represent thechromatic attributes [17]. The decorrelation of R, G and Bcomponent images makes the Y, IandQ component imagescomplementary to each other [17]. The YUV colour spaceis widely used in video and broadcasting today. It is verydifferent from RGB colour space; instead of three largecolour channels, it deals with one brightness or luminancechannel (Y) and two colour or chrominance channels(U-blue and V-red). HSI is the most frequently usedapplication oriented colour space. HSI colour space is basedon the human visual perception theory and is suitable fordescribing, and interpreting colour. H, S and I representhue, saturation and intensity, respectively. The supposedseparation of the luminance component from chrominanceinformation is stated to have advantages in applicationssuch as image processing. Embedding the watermark in theintensity component of HSI colour space can resist theltering, sharpening etc. attacks effectively [18]. In HSVcolour space, the colour is decomposed into hue; saturationand luminance value similar to the way humans tend to

perceive colour. Ledleys research shows that theperformance of HSV colour space is good in colourimproving [19]. Among the three components of HSVcolour space, hue is the attribute of a colour, which decides

which colour it is. For the purpose of enhancing a colourimage, it is to be seen that hue should not change for any

pixel. If hue is changed then the colour gets changed,thereby distorting the image [19]. Compared with other

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perceptually uniform, it is easier to control the hue componentof colour and avoid colour shifting in the HSV colour space.In 1976, the CIE recommended the CIE L*a*b*, or CIELabcolour space for colour quality estimation [20]. The colourspace CIELab is a perceptually uniform colour spacecreated by nonlinear transformations of tristimulus XYZvalues to overcome the non-uniformity of colour spaceswhich had been discussed by Macadam [20]. The main

intention was to provide a standard and approximateuniform colour space which can be used to compare thecolour values easily. In this colour space the differences

between points plotted in the colour space correspond tovisual differences between the colours plotted. The CIErecommended to use XYZ coordinate system to transformRGB to L*a*b*.

4 Arnold transform map

ATM or Arnold transform Map is a kind of image scramblingmethods, called as Arnolds cat mapping. Cause of this nameis that, it is proposed by Vladimir Arnold and it is used on the

image of a cat in Arnolds work, in the 1960s [1]. The discreteArnold transformation is dened as follows [1]

Xn+1Yn+1

=

a b

c d

Xn

Yn

= A

XnYn

mod N (1)

where, a, b, c and d are positive integers, andA| |= ad bc.1, so only three among the four parametersof a, b, c and dare independent. Xn+1, Yn+1, Xn and Yn areintegers in {0,1,2, , N 1}. In this paper the extendedArnold transform in [21] is used to scramble watermarkingof copyright protection.

5 Watermark preprocessing

A digital watermarking system usually consists of embeddingframework and extraction framework. The block diagram ofthe proposed watermarking approach is shown in Fig. 1.

5.1 Embedding framework

The steps involved in the embedding of watermark image intoLL3 coefcients of the host image are described as follows:

Step 1: Convert RGB channels of a host image H into theintended channels.Step 2: Pre-ltering the rst channel.Step 3:Decompose the rst channel into three levels with tenDWT sub-bands, F(Y). The sub-band LL3 is taken as thetarget sub-band for embedding watermarks.Step 4: Creating a sign matrix to save the signs of selectedtarget sub-band coefcients.Step 5: Quantisation of the selected embedding coefcients.Step 6: Divide the target sub-band into the differentsub-blocks. In this paper each sub-block size is equal to 16.Step 7: Determining the maximum message size of eachsub-blocks.Step 8:For more security of watermarks, rst, the watermarkWis scrambled for key times with presented ATM algorithmin [22] and then reshaped to a sequence; after that, a random

binary sequence R of size n is adopted to encrypt thewatermark, where n is the size of the watermark image.This adopting process uses a pseudo-random numbergenerator to determine the pixel to be used on a given key.

Step 9: Embedding the watermark using the correlationproperties of additive pseudo-random noise patternsaccording to equation shown in below:

IW x,y(u,v)= Ix,y+ k

Wi, if W =0

Ix,yWi, Otherwise

(2)

where kdenotes a gain factor for completely controlling the

imperceptibility of watermarked images and the robustnessof watermarks and also Iw is the resulting watermarkedimage.Step 10: Apply the sign matrix.Step 11: Perform inverse DWT on new rst channel with allchanged and unchanged DWT coefcients.Step 12: Reconvert intended channels of the changed hostimage into RGB channels.Step 13: Save key times of ATM, random binary sequence Rand index of the embedded sub-band as the authenticated key.

5.2 Extraction framework

The proposed algorithm is a blind watermarking algorithmand thus the original host image is not required to extractthe watermark. Extraction algorithm is the same asembedding one and pre-ltering is used before applyingDWT transform to better separate watermark informationfrom host image. The watermark extraction procedure isdescribed in details in the following steps:

Step 1: Convert RGB channels of a watermarked image Hinto the intended channels.Step 2: Pre-ltering the rst channel.Step 3:Decompose the rst channel into three levels with tenDWT sub-bands. The sub-band LL3 is taken as the target

sub-band for extraction watermarks.Step 4: Quantisation of the selected embedding coefcients.Step 5: Divide of the target sub-band into the differentsub-blocks.Step 6: Determining the maximum message size of eachsub-blocks.Step 7: Computation of thresholdTas follows

T =Correlation(HL)+Correlation(LH)

2 (3)

Step 8: Computation of the thresholdTand each embeddedcoefcient correlation in sub-blocks, separately.

Step 9: The sequence encrypted watermark is extracted asfollows

Wi =0, if CilT

Wi =1, Otherwise

(4)

Step 10: The encrypted image watermark is produced byreconverting the extracted sequence watermark.Step 11: Scramble the encrypted image watermark with thesame ATM algorithm with the same key times.

6 Experimental results

To achieve the high watermark security, imperceptibilityand robustness against different attacks such asJPEG compression and noise, the proposed perceptualwatermarking scheme was implemented to evaluate the best

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colour space for watermarking algorithms based oncorrelation techniques. Three 512 512 famous images:Lena, peppers and baboon shown in Figs. 2ac were takenas the host images to embed a 15 64 binary watermark

image shown in Fig. 2d. For gain factor k, the value 1.0was taken through implementation of the proposed CDMAscheme. It should be mentioned that in all of theimplementations, MATLAB R2007a software was used.

Fig. 1 Block diagrams of the proposed watermarking approach

a Embedding procedureb Extraction procedure

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Also, nine digit keys used as initial state of MATLABrandom number generator and 79 biorthogonal spline(B-spline) wavelet lters for computation of the wavelettransforms, were used. Cause of using B-spline functionwavelet is that, B-spline functions, do not have compactsupport, but are orthogonal and have better smoothness

properties than other wavelet functions [1].

After watermark embedding process, the similarity oforiginal host images and watermarked images wasmeasured by the standard correlation coefcient (Corr) as[23]

Correlation =

xx

yy

xx( )2

yx 2 (5)

Moreover, the peak signal-to-noise ratio (PSNR) was used toevaluate the quality of the watermarked images as [24]

PSNR= 10log10

2552

MSE(dB) (6)

where mean-square error (MSE) is dened as [24]

MSE =1

mn

mi=1

nj=1

hi,j hi,j

2(7)

where {hi,j} and {hi, j} are the grey levels of pixels in the hostand watermarked images, respectively.

The larger PSNR is, the better the image quality is. Ingeneral, a watermarked image is acceptable by human

perception if its PSNR is >30 dBs. In other words, the

correlation is used for evaluating the robustness ofwatermarking technique and the PSNR is used forevaluating the transparency of watermarking technique [23,24]. Also the normalised correlation (NC) coefcientwas used to measure the similarity between originalwatermarks W and the extracted watermarks W. It wasdened as [21,24]

NC =

i

jwi,jw

i,j

i

jw

2i,j

(8)

Fig.3shows the watermarked images in all colour spaces. Asit can be seen the proposed CDMA watermarking scheme

yields satisfactory results in watermark imperceptibilityand robustness in all colour spaces except HSI and HSVcolour spaces. The results of PSNRs are shown in Table 1.As it is obvious, in proposed watermarking scheme after

JPEG-YCbCr colour space, respectively, RGB, YCbCr,YUV, CIELab and YIQ colour spaces have the greatestPSNR values. It means, performing the proposed method inJPEG-YCbCr colour space and then, respectively, RGB,YCbCr, YUV, CIELab and YIQ colour spaces lead to the

best watermark imperceptibility property.It should be mentioned, because of the different

experimental methods and different parameters the

comparison between different experimental results isdifcult. However, from obtained results, it can be said thatthe proposed algorithm increases imperceptibility propertyin comparing with the similar algorithms in previous workssuch as [2527]. So that, the PSNRs values of watermarkedimage, in [25] are about 48.249 dB for 2472 watermark

bit and in [26] and [27] are, respectively, about 33.234 dBand 3536 dB, for 1024 watermark bit; While, the PSNRsof the watermarked images produced by the proposedscheme are all greater than 67 dB (in baboon in YIQ colourspace) for 960 watermark bit. In addition, NCs betweenoriginal watermark images and extracted watermark imagesin all colour spaces are all equal 1.

After achieving the desired delity, various attacks wereperformed to test the robustness of the proposed schemeand it was found that the proposed scheme performsexcellently robustness against JPEG compression anddifferent noise attacks.

6.1 Robustness to JPEG compression

To evaluate the response of the watermarking scheme toJPEG compression, watermarked images were compressedwith different JPEG quality factors Qs: 10, 15, 25, 50 and75. The overall robustness of proposed scheme for JPEGcompression is considered high level, according to therobustness requirements table provided by Petitcolas [28].

Fig. 4 shows the extracted watermarks from compressedwatermarked images in all colour space after JPEGcompression under quality factor (Q) 15 and Table 2illustrates the related percentage of error bit rates. Also,Fig. 5 shows the percentage of error bit rates of extractedwatermarks from JPEG compression under all JPEG qualityfactors Qs: 10, 15, 25, 50 and 75 in all colour spaces.

As it is obvious, the obtained results show that incomparing with earlier works such as [23, 29], our

proposed scheme improves robustness against JPEGcompression. So that, the percentage of error bit rates ofcompressed watermarked baboon with quality factorQ= 15in [23] is near to 23% and in [29] is near to 50%. While, inour proposed scheme and in the same condition, themaximum value is 17.08% (in JPEG-YCbCr colour space)and minimum equals to 0.3% (in CIELab colour space). Inaddition, by comparing different colour spaces, it can befound that YIQ colour space has the greatest error bit ratevalue and it equals to 28.54%; while after that, respectively,JPEG-YCbCr, YUV, RGB, YCbCr and CIELab colourspaces have the greatest values. It means, performing the

proposed method on CIELab colour space and then,respectively, YCbCr, RGB, YUV, JPEG-YCbCr and YIQcolour spaces lead to the most robustness against JPEGcompression.

6.2 Robustness to noise attacks

The CDMA proposed scheme was tested in all colour spacesfor evaluating its robustness against different noises. This wasdone by rst introducing Gaussian noise with zero mean and

Fig. 2 Experimental results of three famous host images and a

binary watermark image

acHost Lena, peppers and baboon imagesdWatermark image

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different variances 0.11 to noise into the watermarked

images. Fig.6and Table3, respectively, show the extractedwatermarks of different colour spaces under Gaussian noiseof 1% and their percentage of error bit rates. Also, the

percentage of error bit rates of extracted watermarks for

different colour spaces under Gaussian noise with zeromean and different variances: 0.11 are shown in Fig. 7,too. From the results, it can be found that the proposed

Table 1 PSNRs values of watermarked images in differentcolour spaces

Colour space Watermarked images

Lena Peppers Baboon

RGB 94.35 94.26 94.36YCbCr 91.72 91.58 91.72

JPEG-YCbCr 96.36 94.32 94.37YIQ 86.19 72.15 67.12YUV 94.30 84.36 79.77CIELab 77.07 76.82 77.70

Fig. 3 Watermarked images in different colour spaces

Fig. 4 Extracted watermarks from watermarked images in all

colour space after JPEG compression under quality factor Q = 15

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scheme satises robustness against Gaussian noise as welland enhances related results in [23]. So that, in the samecondition, the maximum percentage of error bit rates is35.45% (in RGB colour space) and minimum is 2.6% (in

CIELab colour space) for 960 watermark bit, while in [23],it is about 815% for 1281024 watermark bit.

By comparing all colour spaces, it can be found that thepercentages of error bit rates in RGB colour space aregreatest than the others; whereas after that, respectively,YCbCr and GPEG-YCbCr, YIQ, YUV and CIELab colourspaces have the greatest values. It means, performing the

proposed scheme on CIELab colour space and after that,

respectively, YUV, YIQ, YCbCr and JPEG-YCbCr andRGB colour spaces lead to the most robustness againstGaussian noise attack. It is necessary to note that YCbCrand JPEG-YCbCr colour spaces have the same robustnessagainst Gaussian noise attack.

When the salt and pepper noise with zero mean anddifferent noise densities 0.01 to 0.5 introduced in thewatermarked images, it was found that the proposed CDMAscheme is very efcient in robustness against salt and

Fig. 5 Percentage of error bit rates of extracted watermarks from JPEG compression in all colour spaces

a Lenab Peppersc Baboon

Table 2 Percentage of error bit rates in JPEG experimentunder quality factor Q= 15

Colour space Error bit rate % (Q= 15)

Lena Peppers Baboon

RGB 23.43 23.95 15.93YCbCr 16.14 21.14 12.39JPEG-YCbCr 24.06 26.25 17.08YIQ 25.62 28.54 16.66YUV 25.41 28.33 16.25CIELab 0.1 0.2 0.3

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peppers noise attack. Fig.8shows the extracted watermarks inall colour spaces, from noisy watermarked images under noisedensity N.D = 0.5 and Table4shows the related percentage oferror bit rates.

As it is obvious, the maximum percentage of error bit rateis 28.22% (in RGB colour space). The percentages of error bitrates of extracted watermarks for different colour spacesunder salt and pepper noise with noise densities 0.010.5

Fig. 7 Percentage of error bit rates of extracted watermarks for different colour spaces under Gaussian noise experiment


Fig. 6 Extracted watermarks from Gaussian noise of 1%

Table 3 Percentage of error bit rates in Gaussian noiseexperiment under variance ofV= 1

Colour space Error bit rate % (V= 1)

Lena Peppers Baboon


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Fig. 8 Extracted watermarks from salt and pepper noise

experiment with noise density N.D = 0.5

Fig. 9 Percentage of error bit rate of extracted watermarks for different colour spaces under salt and pepper noise experiment


Table 4 Percentage of error bit rates in salt and pepper noiseexperiment under noise density N.D = 0.5

Colour space Error bit rate % (N.D = 0 .5)

Lena Peppers Baboon


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are illustrated in Fig. 9. From the obtained results it can besaid that, RGB colour space has the greatest values of error

bit rates in comparing with the other colour spaces; whileafter that respectively, YIQ, JPEG-YCbCr, YCbCr, YUVand CIELab have the greatest values. It means that

performing the proposed scheme on CIELab colour spaceand after that respectively, YUV, YCbCr, JPEG-YCbCr,YIQ and RGB colour spaces lead to the most robustness

against salt and pepper noise attack.

7 Conclusions

In this paper a CDMA watermarking scheme which usesDWT2 was proposed and implemented in eight historicalcolour spaces: RGB, YCbCr, JPEG-YCbCr, YIQ, YUV,HSI, HSV and CIELab in order to investigate the inuenceof colour spaces on image watermarking algorithms basedon correlation techniques. The proposed approach exceptHSI and HSV colour spaces satises the watermarkimperceptibility, robustness and security in six other colourspaces: RGB, YCbCr, JPEG-YCbCr, YIQ, YUV andCIELab much better than the earlier works. The lowestPSNR value of the host images belongs to YIQ colourspace and is greater than 67 dB and all NCs of extractedwatermarks from watermarked images are 1. The obtainedresults of extracted watermarks from JPEG-compression(even if quality factor is low) and also Gaussian and saltand pepper noises (even in high noisy attacks) aresatisfactory. The observations regarding the proposedwatermarking scheme are summarised as follows:

The watermarking security is more satisfactory thanthe earlier works such as [23]; so that, the watermark Wis scrambled by ATM and after converting to a sequence,

is adopted with a random binary sequence using apseudo-random number generator to encrypt the watermark.In addition, embedding watermark in the intended channelof each colour space, increased security property, too. Except HSI and HSV colour spaces, the proposed approachimproves watermark imperceptibility in all colour spacesmore than the obtained results in [2527] and enhancesrobustness against JPEG compression and Gaussian noiseattack, respectively more than the obtained results in [23,29] and [23]. In correlation based watermarking techniques,JPEG-YCbCr colour spaces satisfy the imperceptibility

property more than the other colour spaces. After that,respectively, RGB, YCbCr, YUV, CIELab and YIQ colourspaces satisfy this property. The CDMA proposed approach satises high robustnessagainst JPEG compression. In addition, CIELab colourspace has the most robustness against JPEG compression incorrelation-based watermarking techniques in related to theothers. Then, respectively, YCbCr, RGB, YUV,JPEG-YCbCr and YIQ colour spaces have the mostrobustness. In correlation-based watermarking techniques, CIELabcolour space has the most robustness against Gaussian noiseattack in comparing with the other colour spaces. AfterCIELab colour space, YUV, YIQ, YCbCr & JPEG-YCbCrand RGB colour spaces have the most robustness.

The proposed scheme satises robustness against salt andpepper noise attack as well. In addition, CIELab colourspace has the most related robustness in correlation-basedwatermarking techniques compared with the other colour

spaces. Then, YUV, YCbCr, JPEG-YCbCr, YIQ and RGBcolour spaces satises this requirement.

8 References

1 Fan, L., Gao, T.:A novel blind robust watermarking scheme based on

statistic characteristic of wavelet domain coefcients. Proc. Int. Conf.Signal Processing Systems, Tianjin, China, May 2009, pp. 1211252 Wang, X., Zhang, X.P.: Optimal look-up table-based data hiding,IET

Signal Process., 2011, 5 , (2), pp. 1711793 Lin, Y., Abdulla, W.: Objective quality measures for perceptual

evaluation in digital audio watermarking, IET Signal Process., 2011,5, (7), pp. 623631

4 Ansari, R., Devanalamath, M.M., Manikanta, K., Ramachandran, S.:Robust digital image watermarking algorithm in DWT-DFT-SVDdomain for color images. Proc. Int. Conf. Communication,Information & Computing Technology, Mumbai, India, October 2012,pp. 16

5 Li, L., Xu, H.H., Chang, C.C., Ma, Y.Y.:A novel image watermarkingin redistributed invariant wavelet domain,J. Syst. Softw., 2011, 84, (6),pp. 923929

6 Chen, S.T., Huang, H.N., Chen, C.J.,, Wu, G.D.: Energy-proportionbased scheme for audio watermarking, IET Signal Process., 2010, 4,

(5), pp. 5765877 Chen, S.T., Wu, G.D., Huang, H.N.: Wavelet-domain audio

watermarking scheme using optimisation-based quantisation, IETSignal Process., 2010, 4 , (6), pp. 720727

8 Preda, R.O., Vizireanu, D.N.:A robust digital watermarking scheme forvideo copyright protection in the wavelet domain, Measurement, 2010,43, (10), pp. 7201726

9 Preda, R.O., Vizireanu, D.N.: Quantisation-based video watermarkingin the wavelet domain with spatial and temporal redundancy,Int. J. Electron., 2011, 98, (3), pp. 393405

10 Preda, R.O., Vizireanu, D.N.: Robust wavelet-based videowatermarking scheme for copyright protection using the human visualsystem, J. Electron. Imaging, 2011, 20 , (1), pp. 013022

11 Deng, N., Jiang, C.S.: CDMA watermarking algorithm based onwavelet basis. Proc. Ninth Int. Con. Fuzzy Systems and KnowledgeDiscovery, May 2012, pp. 21482152

12 Wirth, M., Nikitenko, D.:

The effect of color space on imagesharpening algorithms. Proc. Canadian Conf. Computer and RobotVision, Guelph, Canada, MayJune 2010, pp. 7985

13 Bhattacharya, T., Hore, S., Dey, N., Chaudhuri, S.R.B.: Analysis of anovel audio hash function based upon stationary wavelet transform.Proc. Second Int. Conf. Computational Science, Engineering andInformation Technology, Tamil Nadu, India, October 2012, pp.575579

14 Kim, S.H., Lee, K.H., Lee, Y.H., Ha, H.Y.:Digital watermarking basedon color differences. Proc. SPIE, Security and Watermarking ofMultimedia Contents III, August 2001, vol. 4314, pp. 1017

15 Lusson, F., Bailey, K., Leeney, M., Curran, K.: A novel approach todigital watermarking, exploiting colour spaces, Signal Process., 2013,93, (5), pp. 12681294

16 Khalili, M., Asatryan, D.:A improved DWT based watermarking usingJPEG-YCbCr. Proc. Eighth Int. Conf. Computer Science andInformation Technologies, Yerevan, Armenia, August 2011, pp.

21321617 Jiao, Z., Xu, B.: An image enhancement approach using retinex and

YIQ. Proc. Int. Conf. Information Technology and ComputerScience, Wuxi, China, July 2009, vol. 1, pp. 476479

18 Kong, F., Peng, Y.:Color image watermarking algorithm based on HSIcolor space. Proc. Second Int. Conf. Industrial and InformationSystems, Tianjin, China, July 2010, vol. 2, pp. 464467

19 Naik, S.K., Murthy, C.A.: Hue-preserving color image enhancementwithout gamut problem, IEEE Trans. Image Process., 2003, 12, (12),pp. 15911598

20 Kaganami, H.G., Beiji, Z., Soliman, M.S.: Advanced color imagesenhancement using wavelet and K-means clustering. Proc. Fifth Int.Conf. Intelligent Information Hiding and Multimedia SignalProcessing, Changsha, China, September 2009, pp. 648652

21 Khalili, M.:A comparison between digital images watermarking in twodifferent color spaces using DWT2. Proc. Seventh Int. Conf. Computer

Science and Information Technologies, Yerevan, Armenia, September

October 2009, pp. 15816222 Wei, Y., Hao, Y., Li, H.: A multipurpose digital watermarking

algorithm of color image. Proc. Int. Conf. Mechatronics andAutomation, Harbin, China, August 2009, pp. 112117

www.ietdl.org




11/11

23 Fang, Y., Huang, J., Shi, Y.Q.: Image Watermarking AlgorithmApplying CDMA. Proc. Int. Symp. Circuits and Systems,Guangzhou, China, May 2003, vol. 2, pp. II-948II-951

24 Rao, N.V., Kumari, M.:Watermarking in medical imaging for securityand authentication, Inf. Secur. J., Glob. Perspect., 2011, 20, (3), pp.148155

25 Yang, S., Song, Z., Fang, Z., Yang, J.:A novel afne attack robust blindwatermarking algorithm. Proc. Symp. Security Detection andInformation Processing, Procedia Engineering, 2010, vol. 7, pp.239246

26 Pradhan, C., Rath, S., Bisoi, A.K.: Non blind digital watermarkingtechnique using DWT and cross chaos. Proc. Second Int. Conf.

Communication, Computing & Security, Roukela, India, October2012, vol. 6, pp. 897904

27 Zhang, F., Yang, G., Liu, X., Zhang, X.: Image watermarkingalgorithm based on the code division multiple access technique.Knowledge-Based Intelligent Information and Engineering Systems,2006, (LNCS, 4252), pp. 204211

28 Petitcolas, F.A.P.: Watermarking schemes evaluation, IEEE SignalProcess. Mag., 2000, 17, (5), pp. 5864

29 Fang, Y., Gu, L., Huang, J.: Performance analysis ofCDMA-based watermarking with quantization scheme.

Information Security Practice and Experience, 2005, (LNCS,3439), pp. 350361

www.ietdl.org



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