342 research outputs found

    Entropy Based Robust Watermarking Algorithm

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    TĂ€nu aina kasvavale multimeedia andmeedastus mahtudele Internetis, on esile kerkinud mured turvalisusest ja piraatlusest. Digitaalse meedia paljundamise ja muutmise maht on loonud vajaduse digitaalse meedia vesimĂ€rgistamise jĂ€rgi. Selles töös on tutvustatud vastupidavaid vesimĂ€rkide lisamise algoritme, mis lisavad vesimĂ€rgid madala entroopiaga pildi osadesse. VĂ€lja pakutud algoritmides jagatakse algne pilt blokkidesse ning arvutatakse iga bloki entroopia. KĂ”ikide blokkide keskmine entroopia vÀÀrtus valitakse kĂŒnniseks, mille jĂ€rgi otsustatakse, millistesse blokkidesse vesimĂ€rk lisada. KĂ”ik blokid, mille entroopia on vĂ€iksem kui kĂŒnnis, viiakse signaali sageduse kujule kasutades Discrete Wavelet Transform algoritmi. Madala sagedusega sagedusvahemikule rakendatakse Chirp Z-Transform algoritmi ja saadud tulemusele LU-dekompositsiooni vĂ”i QR-dekompositsiooni. Singular Value Decomposition meetodi rakendamisel diagonaalmaatriksile, mis saadi eelmisest sammust, saadakse iga bloki vastav vÀÀrtus. VesimĂ€rk lisatakse pildile, liites iga bloki arvutatud vÀÀrtusele vesimĂ€rgi Singular Value Decomposition meetodi tulemused. Kirjeldatud algoritme testiti ning vĂ”rreldi teiste tavapĂ€rast ning uudsete vesimĂ€rkide lisamise tehnoloogiatega. Kvantitatiivsed ja kvalitatiivsed eksperimendid nĂ€itavad, et vĂ€lja pakutud meetodid on tajumatud ning vastupidavad signaali töötlemise rĂŒnnakutele.With growth of digital media distributed over the Internet, concerns about security and piracy have emerged. The amount of digital media reproduction and tampering has brought a need for content watermarking. In this work, multiple robust watermarking algorithms are introduced. They embed watermark image into singular values of host image’s blocks with low entropy values. In proposed algorithms, host image is divided into blocks, and the entropy of each block is calculated. The average of all entropies indicates the chosen threshold value for selecting the blocks in which watermark image should be embedded. All blocks with entropy lower than the calculated threshold are decomposed into frequency subbands using discrete wavelet transform (DWT). Subsequently chirp z-transform (CZT) is applied to the low-frequency subband followed by an appropriate matrix decomposition such as lower and upper decomposition (LUD) or orthogonal-triangular decomposition (QR decomposition). By applying singular value decomposition (SVD) to diagonal matrices obtained by the aforementioned matrix decompositions, the singular values of each block are calculated. Watermark image is embedded by adding singular values of the watermark image to singular values of the low entropy blocks. Proposed algorithms are tested on many host and watermark images, and they are compared with conventional and other state-of-the-art watermarking techniques. The quantitative and qualitative experimental results are indicating that the proposed algorithms are imperceptible and robust against many signal processing attacks

    Maximum Energy Subsampling: A General Scheme For Multi-resolution Image Representation And Analysis

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    Image descriptors play an important role in image representation and analysis. Multi-resolution image descriptors can effectively characterize complex images and extract their hidden information. Wavelets descriptors have been widely used in multi-resolution image analysis. However, making the wavelets transform shift and rotation invariant produces redundancy and requires complex matching processes. As to other multi-resolution descriptors, they usually depend on other theories or information, such as filtering function, prior-domain knowledge, etc.; that not only increases the computation complexity, but also generates errors. We propose a novel multi-resolution scheme that is capable of transforming any kind of image descriptor into its multi-resolution structure with high computation accuracy and efficiency. Our multi-resolution scheme is based on sub-sampling an image into an odd-even image tree. Through applying image descriptors to the odd-even image tree, we get the relative multi-resolution image descriptors. Multi-resolution analysis is based on downsampling expansion with maximum energy extraction followed by upsampling reconstruction. Since the maximum energy usually retained in the lowest frequency coefficients; we do maximum energy extraction through keeping the lowest coefficients from each resolution level. Our multi-resolution scheme can analyze images recursively and effectively without introducing artifacts or changes to the original images, produce multi-resolution representations, obtain higher resolution images only using information from lower resolutions, compress data, filter noise, extract effective image features and be implemented in parallel processing

    DCT Implementation on GPU

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    There has been a great progress in the field of graphics processors. Since, there is no rise in the speed of the normal CPU processors; Designers are coming up with multi-core, parallel processors. Because of their popularity in parallel processing, GPUs are becoming more and more attractive for many applications. With the increasing demand in utilizing GPUs, there is a great need to develop operating systems that handle the GPU to full capacity. GPUs offer a very efficient environment for many image processing applications. This thesis explores the processing power of GPUs for digital image compression using Discrete cosine transform

    Lossless and low-cost integer-based lifting wavelet transform

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    Discrete wavelet transform (DWT) is a powerful tool for analyzing real-time signals, including aperiodic, irregular, noisy, and transient data, because of its capability to explore signals in both the frequency- and time-domain in different resolutions. For this reason, they are used extensively in a wide number of applications in image and signal processing. Despite the wide usage, the implementation of the wavelet transform is usually lossy or computationally complex, and it requires expensive hardware. However, in many applications, such as medical diagnosis, reversible data-hiding, and critical satellite data, lossless implementation of the wavelet transform is desirable. It is also important to have more hardware-friendly implementations due to its recent inclusion in signal processing modules in system-on-chips (SoCs). To address the need, this research work provides a generalized implementation of a wavelet transform using an integer-based lifting method to produce lossless and low-cost architecture while maintaining the performance close to the original wavelets. In order to achieve a general implementation method for all orthogonal and biorthogonal wavelets, the Daubechies wavelet family has been utilized at first since it is one of the most widely used wavelets and based on a systematic method of construction of compact support orthogonal wavelets. Though the first two phases of this work are for Daubechies wavelets, they can be generalized in order to apply to other wavelets as well. Subsequently, some techniques used in the primary works have been adopted and the critical issues for achieving general lossless implementation have solved to propose a general lossless method. The research work presented here can be divided into several phases. In the first phase, low-cost architectures of the Daubechies-4 (D4) and Daubechies-6 (D6) wavelets have been derived by applying the integer-polynomial mapping. A lifting architecture has been used which reduces the cost by a half compared to the conventional convolution-based approach. The application of integer-polynomial mapping (IPM) of the polynomial filter coefficient with a floating-point value further decreases the complexity and reduces the loss in signal reconstruction. Also, the “resource sharing” between lifting steps results in a further reduction in implementation costs and near-lossless data reconstruction. In the second phase, a completely lossless or error-free architecture has been proposed for the Daubechies-8 (D8) wavelet. Several lifting variants have been derived for the same wavelet, the integer mapping has been applied, and the best variant is determined in terms of performance, using entropy and transform coding gain. Then a theory has been derived regarding the impact of scaling steps on the transform coding gain (GT). The approach results in the lowest cost lossless architecture of the D8 in the literature, to the best of our knowledge. The proposed approach may be applied to other orthogonal wavelets, including biorthogonal ones to achieve higher performance. In the final phase, a general algorithm has been proposed to implement the original filter coefficients expressed by a polyphase matrix into a more efficient lifting structure. This is done by using modified factorization, so that the factorized polyphase matrix does not include the lossy scaling step like the conventional lifting method. This general technique has been applied on some widely used orthogonal and biorthogonal wavelets and its advantages have been discussed. Since the discrete wavelet transform is used in a vast number of applications, the proposed algorithms can be utilized in those cases to achieve lossless, low-cost, and hardware-friendly architectures

    Robust digital image watermarking algorithms for copyright protection

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    Digital watermarking has been proposed as a solution to the problem of resolving copyright ownership of multimedia data (image, audio, video). The work presented in this thesis is concerned with the design of robust digital image watermarking algorithms for copyright protection. Firstly, an overview of the watermarking system, applications of watermarks as well as the survey of current watermarking algorithms and attacks, are given. Further, the implementation of feature point detectors in the field of watermarking is introduced. A new class of scale invariant feature point detectors is investigated and it is showed that they have excellent performances required for watermarking. The robustness of the watermark on geometrical distortions is very important issue in watermarking. In order to detect the parameters of undergone affine transformation, we propose an image registration technique which is based on use of the scale invariant feature point detector. Another proposed technique for watermark synchronization is also based on use of scale invariant feature point detector. This technique does not use the original image to determine the parameters of affine transformation which include rotation and scaling. It is experimentally confirmed that this technique gives excellent results under tested geometrical distortions. In the thesis, two different watermarking algorithms are proposed in the wavelet domain. The first algorithm belongs to the class of additive watermarking algorithms which requires the presence of original image for watermark detection. Using this algorithm the influence of different error correction codes on the watermark robustness is investigated. The second algorithm does not require the original image for watermark detection. The robustness of this algorithm is tested on various filtering and compression attacks. This algorithm is successfully combined with the aforementioned synchronization technique in order to achieve the robustness on geometrical attacks. The last watermarking algorithm presented in the thesis is developed in complex wavelet domain. The complex wavelet transform is described and its advantages over the conventional discrete wavelet transform are highlighted. The robustness of the proposed algorithm was tested on different class of attacks. Finally, in the thesis the conclusion is given and the main future research directions are suggested

    Discrete Wavelet Transforms

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    The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

    A NOVEL JOINT PERCEPTUAL ENCRYPTION AND WATERMARKING SCHEME (JPEW) WITHIN JPEG FRAMEWORK

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    Due to the rapid growth in internet and multimedia technologies, many new commercial applications like video on demand (VOD), pay-per-view and real-time multimedia broadcast etc, have emerged. To ensure the integrity and confidentiality of the multimedia content, the content is usually watermarked and then encrypted or vice versa. If the multimedia content needs to be watermarked and encrypted at the same time, the watermarking function needs to be performed first followed by encryption function. Hence, if the watermark needs to be extracted then the multimedia data needs to be decrypted first followed by extraction of the watermark. This results in large computational overhead. The solution provided in the literature for this problem is by using what is called partial encryption, in which media data are partitioned into two parts - one to be watermarked and the other is encrypted. In addition, some multimedia applications i.e. video on demand (VOD), Pay-TV, pay-per-view etc, allow multimedia content preview which involves „perceptual‟ encryption wherein all or some selected part of the content is, perceptually speaking, distorted with an encryption key. Up till now no joint perceptual encryption and watermarking scheme has been proposed in the literature. In this thesis, a novel Joint Perceptual Encryption and Watermarking (JPEW) scheme is proposed that is integrated within JPEG standard. The design of JPEW involves the design and development of both perceptual encryption and watermarking schemes that are integrated in JPEG and feasible within the „partial‟ encryption framework. The perceptual encryption scheme exploits the energy distribution of AC components and DC components bitplanes of continuous-tone images and is carried out by selectively encrypting these AC coefficients and DC components bitplanes. The encryption itself is based on a chaos-based permutation reported in an earlier work. Similarly, in contrast to the traditional watermarking schemes, the proposed watermarking scheme makes use of DC component of the image and it is carried out by selectively substituting certain bitplanes of DC components with watermark bits. vi ii Apart from the aforesaid JPEW, additional perceptual encryption scheme, integrated in JPEG, has also been proposed. The scheme is outside of joint framework and implements perceptual encryption on region of interest (ROI) by scrambling the DCT blocks of the chosen ROI. The performances of both, perceptual encryption and watermarking schemes are evaluated and compared with Quantization Index modulation (QIM) based watermarking scheme and reversible Histogram Spreading (RHS) based perceptual encryption scheme. The results show that the proposed watermarking scheme is imperceptible and robust, and suitable for authentication. Similarly, the proposed perceptual encryption scheme outperforms the RHS based scheme in terms of number of operations required to achieve a given level of perceptual encryption and provides control over the amount of perceptual encryption. The overall security of the JPEW has also been evaluated. Additionally, the performance of proposed separate perceptual encryption scheme has been thoroughly evaluated in terms of security and compression efficiency. The scheme is found to be simpler in implementation, have insignificant effect on compression ratios and provide more options for the selection of control factor

    Connected Attribute Filtering Based on Contour Smoothness

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