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A remote sensing image self-adaptive blind watermarking algorithm based on wavelet transformation
Abstract
Based on the statistical characters of remote sensing image, this paper proposed firstly partition remote sensing image into sub-block images of suitable sizes, and then decomposing these sub-block images with biorthogonal 7/5 wavelet. A novel construction method of wavelet set of coefficients is adopted to embed binary watermarking image into sub-bands except low frequency sub-bands, and realizing a blind detection algorithm. The visual model of biorthogonal 9/7 wavelet is extended to construct a visual weighted analysis method based on the biorthogonal 7/5 wavelet domain quantization noises, thus making the strength of the embedded watermarking could self-adapt to the sub-blocks of the remote sensing image. Experimental results show that the proposed algorithm has great imperceptibility and is robust to the image intensity attack such as geometric transformation, noise adding, filtering, and compression. It performs better than that of the watermarking algorithm proposed by Ho in the robust, and being a practical blind watermarking algorithm.
... 38 Wang et al proposed a DCT-based method to put the watermark in the middle frequency coefficients and make the watermark insertion process nearly lossless. 39 Lei et al embedded the watermark in the singular values of low-frequency coefficients based on QWT to improve watermark robustness. 19 As we all know, the high-frequency coefficients correspond to detailed information, while the low-frequency coefficients occupy most of the energy of the image and correspond to large-scale features; therefore, the latter is more stable and is less disturbed by external factors. ...
Digital watermarking is important for protecting the intellectual property of remote sensing images. Unlike watermarking in ordinary colour images, in colour remote sensing images, watermarking has an important requirement: robustness. In this paper, a robust nonblind watermarking scheme for colour remote sensing images, which considers both frequency and statistical pattern features, is constructed based on the quaternion wavelet transform (QWT) and tensor decomposition. Using the QWT, not only the abundant phase information can be used to preserve detailed host image features to improve the imperceptibility of the watermark, but also the frequency coefficients of the host image can provide a stable position to embed the watermark. To further strengthen the robustness, the global statistical feature structure acquired through the tensor Tucker decomposition is employed to distribute the watermark's energy among different colour bands. Because both the QWT frequency coefficients and the tensor decomposition global statistical feature structure are highly stable against external distortion, their integration yields the proposed scheme, which is robust to many image manipulations. A simulation experiment shows that our method can balance the trade‐off between imperceptibility and robustness and that it is more robust than the traditional QWT and discrete wavelet transform (DWT) methods under many different types of image manipulations.
... Data hiding has grown ever since and utterly transformed; while it originated as an instinctive art, it now became a well-defined science with its own resourceful schemes. To name a few amongst its innumerable applications, data hiding is employed in medical [8] [12] [27], military [23], national security [48], forensics [47] [48], fingerprinting [2], broadcast monitoring [14], copyright authentication [22] [29], land consolidation [30], individuals, etc. Nonetheless, there is still an overlooked perplexity when watermarking is mentioned with steganography and cryptography. Actually these labels or tags are closely interrelated and constitute a multifaceted core. ...
This paper presents a new methodology for data hiding using digital watermarking in the DCT Domain. The methodology relies on a new scheme for encrypting the data prior to the embedding stage. The key used for ciphering is almost of arbitrary length, type and format; this endows the watermark with a powerful, 3-level reinforced security structure. It is a blind-detector watermarking technique and the amount of the hidden data is increased by 60% compared with the traditional AC-Coefficients Prediction algorithm while sustaining a high level of transparency. Simulation results were carried out which demonstrated a promising PSNR, limited blocking artifacts, and a satisfactory level of the overall performance. The paper also presents an extensive survey of prominent digital-watermarking research outcomes in the WSEAS Transactions.
... For many years, multi-scale representations and multiresolution analysis have proved useful in many signal processing applications. Wavelet analysis is an example to generate such representation [4, 5, 6]. In [6], Wang et al. proposed a digital audio watermarking algorithm based on the discrete wavelet transform (DWT). ...
In this paper, we propose a new approach for optimization in digital audio watermarking using artificial intelligent technique. The watermarks are embedded into the low frequency coefficients in discrete multiwavelet transform domain. The embedding technique is based on quantization process which does not require the original audio signal in the watermark extraction. We have developed an optimization technique using the genetic algorithm to search for optimal quantization step in order to improve both quality of watermarked audio and robustness of the watermark. In addition, we analyze the performance of the proposed algorithm in terms of signal-to-noise ratio, normalized correlation and bit error rate. The experimental results show that our proposed method can improve the quality of the watermarked audio signal and give more robustness of the watermark as compared to previous works.
... Therefore transform domain watermarking techniques also have been become popular, because such watermarking techniques can avoid computational cost of domain transformation. For more information refer [2], [3] for DCT based watermarking and [13], [14] for DWT based domain. However at current, DCT based compressions can be consider as widely used, because popular H.261/2/3, MPEG-1/2/4, HDTV and CMTT.723 are based on DCT based transformation. ...
Digital watermarking was commenced to copyright protection and ownership verification of multimedia data. However the evolution of the watermark focused on different security aspects of multimedia data such as integrity and authenticity. Fragile and semi-fragile watermarking schemes were introduced to accomplish these requirements. In this paper, we propose semi-fragile watermarking scheme to authenticate visual content of the image. The proposed method is carried out in DCT domain and authenticating the particular number of low frequency coefficient, it achieves the integrity of the image. Since low frequency coefficients carry the essence of the visual data, authenticating only the low frequency data is adequate. Therefore the proposed technique is efficient than the others, which are processing in all DCT coefficients. Digital signature is generated by following the definition of elliptic curve digital signature algorithm (ECDSA). Thus, the scheme is faster than RSA based authentication definition and it provides high level of security and availability. Additionally our scheme localizes the compromised area of the image. Embedded and visual data are protected from quantization of JPEG by altering the quantization table. However the degradation of compression ratio due to alternation in quantization table has been evaluated. Experimental results show that the watermark does not make any visual artifact in original data and it gives evidence that compression ratio degradation is ignorable for average JPEG quality factors.
... There are numerous applications of wavelet theory in image processing like for example watermarking [1, 2], content-based image retrieval [3] or image compression [4]. Another application of the wavelets theory in image processing is the denoising. ...
We propose the use of a new implementation of the hyperanalytic wavelet transform, (HWT), in association with a Maximum a Posteriori (MAP) filter named bishrink. The denoising methods based on wavelets are sensitive to the selection of the mother wavelets. Taking into account the drawbacks of the bishrink filter and the sensitivity with the selection of the mother wavelets we propose a denoising method in two stages in a multi-wavelet context. It is based on diversification followed by wavelet fusion. Some simulation examples and comparisons prove the performances of the proposed method.
Digital Watermarking allows an individual to add some hidden copyright notices or other verification messages to digital media, where message is a group of bits describing the information pertaining to the signal or its author. For this purpose, two techniques viz. global watermarking and local watermarking can be used. In this paper, the performance of two feature based global and local watermarking techniques using Zernike Moments(ZMs) have been analyzed by evaluating their robustness against geometric, photometric and other signal processing attacks including rotation, cropping and noise. Experimental results have been provided in order to compare ZMs based global and local watermarking techniques for different types of attacks. Recommendations have been made based on the comparison of these techniques with other existing works.
In order to combine the copyright protection with the content authentication commendably in the digital watermark, this paper proposes an improved error correction coding -based multipurpose method where the authentication watermark and the robust watermark are embedded in the different coefficients of DCT transform domain respectively. In addition, to strengthen the security, the method still utilizes the error correction coding. Through a series of experiment, the invisibility of the method can be proved both from the PSNR value (PSNR=51.2 dB) and the histogram equalization. The similarity between the original watermark and extracted watermark is almost above 95%. The proposed method is effective in image authentication and it's robust against some image processing operations, such as low-pass filtering, Gaussian noise, JPEG lossy compression, cropping and histogram equalization.
This paper suggested a new efficient lossless compression algorithm for vector maps in view of the graphical characteristics. First, we adopt the differential lossless transformation for the graphic data in the vector map files, to make the original data which should have been represented by double model or float model be represented by long model. Then, based on the abbreviated compression, the prediction coding based on the irregular coefficients is used. Namely, it is to dynamically distribute proper byte storage to the transformed coefficients which have been differentiated according to the numerical values, and compressed further combined with a dictionary coding method. Finally, we do an experimental contrast for the compression effect.
The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Earth observation missions have recently attracted a growing interest, mainly due to the large number of possible applications capable of exploiting remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products. Such a need is a very crucial one, because the Internet and other public/private networks have become preferred means of data exchange. A critical issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: assessment of the requirements imposed by remote sensing applications on watermark-based copyright protection, and modification of two well-established digital watermarking techniques to meet such constraints. More specifically, the concept of near-lossless watermarking is introduced and two possible algorithms matching such a requirement are presented. Experimental results are shown to measure the impact of watermark introduction on a typical remote sensing application, i.e., unsupervised image classification. (C) 2002 Society of Photo-Optical Instrumentation Engineers.
In this paper, a novel digital watermarking technique for
copyright protection of satellite images is presented. This robust
technique can survive a number of image manipulations or "attacks" such
as contrast stretching, rotation, clipping and filtering to the
watermarked image. Conventional digital watermarking techniques use a
number of bits or characters to be embedded into the image. However,
many of these techniques would yield to some minor attacks to the
watermarked image due to the alteration of the values of these bits or
characters. As a result, the legal ownership of the data under copyright
protection would be questionable. The performance of any digital
watermarking algorithms depends on the tradeoff between data integrity
and the robustness of the algorithms
A novel adaptive discrete cosine transform-domain watermarking algorithm is presented for copyrighting of remote sensing images. The proposed method can utilize the human visual system (HVS) to embed a digital watermark in discrete cosine transform middle-high frequency coefficients of host image by scrambling the watermark image, determining adaptively the location where the watermark can be hidden, and modifying intelligently the strength of the embedded watermark. Experimental results show that the novel watermarking scheme for remote sensing image has great imperceptibility and is robust to the image intensity attack such as cropping, high compression, filtering, noise adding, image enhancement, and mosaic. It performs better than that of the watermarking algorithm proposed by Ho in the aspects of imperceptibility and robustness.
We consider the properties of the F(st) measure of genetic divergence between an admixed population and its parental source populations. Among all possible populations admixed among an arbitrary set of parental populations, we show that the value of F(st) between an admixed population and a specific source population is maximized when the admixed population is simply the most distant of the other source populations. For the case with only two parental populations, as a function of the admixture fraction, we further demonstrate that this F(st) value is monotonic and convex, so that F(st) is informative about the admixture fraction. We illustrate our results using example human population-genetic data, showing how they provide a framework in which to interpret the features of F(st) in admixed populations.
We present a watermarking procedure to embed copyright protection into digital audio by directly modifying the audio samples. Our audio-dependent watermarking procedure directly exploits temporal and frequency perceptual masking to guarantee that the embedded watermark is inaudible and robust. The watermark is constructed by breaking each audio clip into smaller segments and adding a perceptually shaped pseudo-random sequence. The noise-like watermark is statistically undetectable to prevent unauthorized removal. Furthermore, the author representation we introduce resolves the deadlock problem. We also introduce the notion of a dual watermark: one which uses the original signal during detection and one which does not. We show that the dual watermarking approach together with the procedure that we use to derive the watermarks effectively solves the deadlock problem. We also demonstrate the robustness of that watermarking procedure to audio degradations and distortions, e.g., those that result from colored noise, MPEG coding, multiple watermarks, and temporal resampling.
Arnold transformation is applied widely in digital image encryption because of its periodicity. But if its periodicity is used in the course of image decryption, it will waste lots of time. So this paper offers a new anti- Arnold transformation algorithm. The algorithm gets anti-Arnold transformation by solving equation groups. The application of Arnold transformation from square image to rectangle image is generalized and its application on image encryption expanded. At the same time, the anti-Arnold transformation from 2-dimension to m-dimension is also generalized.
In this article, we proposed an effective adaptive 2-dimension blind watermarking algorithm based on feature of a remote sensing image. This algorithm exploited a gray image as the watermark, pretreated the watermark image by Arnold confusion and wavelet compression, and embedded it into the selected subband of wavelet transformation domain of the remote sensing image according to neighboring symbol's mean value and odd-even adjugement rule, moreover, detected watermarks without the original remote sensing image. The attack analysis and experimental results show that the watermarking algorithm is transparent and robust, with accurate watermark detecting results and low complexity, and it also has strong robustness against various image attacks such as JPEG lossy compression, median filtering, additive noise, scaling, cropping, rotation, random geometrical attack and Stirmark attack. Furthermore, after embedding watermarks, there is almost no influence on such applications of the remote sensing image as edge detection and image classification.
The demand for remote sensing data has increased dramatically mainly due to the large number of possible applications capable to exploit remotely sensed data and images. As in many other elds, along with the increase of market potential and product diiusion, the need arises for some sort of protection of the image products from unauthorized use. Such a need is a very crucial one even because the Internet and other publiccprivate networks have become preferred and eeective means of data exchange. An important issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. Before applying watermarking techniques developed for multimedia applications to remote sensing applications, it is important that the requirements imposed by remote sensing imagery are carefully analyzed to investigate whether they are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: i assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection; ii discussion of a case study where the performance of two popular, state-of-the-art watermarking techniques are evaluated by the light of the requirements at the previous point.
Earth observation missions have recently attracted a growing interest from the scientific and industrial communities, mainly due to the large number of possible applications capable to exploit remotely sensed data and images. Along with most remote sensing imagery now available in digital form, which can be easily copied and distributed through the Internet, the need of copyright protection arises as well. Such a problem has been largely addressed by resorting to image watermarking technology. We present a novel watermarking method based on a chaotic spread spectrum and apply it to the image products of remote sensing. The correlation property of chaotic sequences is analyzed. It is shown that the chaotic signal is more suitable to provide remote sensing image watermarks. In the retrieval process, the information signal is extracted by using a standard correlator. Experimental results show that the proposed chaotic watermarking system for remote sensing images is robust to various image manipulations, including resizing, cropping, filtering, and compression. Compared to the conventional spread spectrum watermarking approach, the proposed chaotic watermark is superior.
The LeGall 5/3 and Daubechies 9/7 filters have risen to special prominence because they were selected for inclusion in the JPEG2000 standard. We determine their key mathematical features: Riesz bounds, order of approximation, and regularity (Hölder and Sobolev). We give approximation theoretic quantities such as the asymptotic constant for the L2 error and the angle between the analysis and synthesis spaces which characterizes the loss of performance with respect to an orthogonal projection. We also derive new asymptotic error formulae that exhibit bound constants that are proportional to the magnitude of the first nonvanishing moment of the wavelet. The Daubechies 9/7 stands out because it is very close to orthonormal, but this turns out to be slightly detrimental to its asymptotic performance when compared to other wavelets with four vanishing moments.
The 2-D orthogonal wavelet transform decomposes images into both spatial and spectrally local coefficients. The transformed coefficients were coded hierarchically and individually quantized in accordance with the local estimated noise sensitivity of the human visual system (HVS). The algorithm can be mapped easily onto VLSI. For the Miss America and Lena monochrome images, the technique gave high to acceptable quality reconstruction at compression ratios of 0.3-0.2 and 0.64-0.43 bits per pixel (bpp), respectively.
Copyright protection of remote sensing imagery by means of digital watermarking In: Proceedings of the SPIE-The International Society for Optical Engineering Image compression using the 2-D wavelet transform
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Robust audio watermarking using perceptual marking Acknowledgment This work is supported in part by the grand foundation of science and technology department of Zhejiang province under grant No. 2006C13098, the key foundation of education department of Zhejiang province under grant No
- M D Swanson
M. D. Swanson. Robust audio watermarking using perceptual marking. Signal Processing, 66(3), 1998, pp: 337-355. Acknowledgment This work is supported in part by the grand foundation of science and technology department of Zhejiang province under grant No. 2006C13098, the key foundation of education department of Zhejiang province under grant No. 20050642. Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing, Beijing, China, September 15-17, 2007 82
Integer wavelet transformation based full-color compression technology on remote sensing image. Doctor dissertation of Graduate University of the Chinese Academy of Sciences
- Wenjun Sun
WenJun Sun. Integer wavelet transformation
based full-color compression technology on
remote sensing image. Doctor dissertation of
Graduate University of the Chinese Academy of
Sciences. 2003.