外文翻译及文献--基于子带离散余弦变换DCT应用于图像水印的技术-其他专业.doc

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The watermark is casted in a selected number of coefficients of all four bands of a one-level decomposition. A great number of coefficients is being used. Each band gives a different detection output. The result is taken as the average detection result of all bands. It is shown that the final result is better than the detection output of each individual band, thus leading to a very robust watermarking scheme.1. INTRODUCTIONThe great spread of digital media in nowadays, has urged for the protection of the intellectual property rights of the creators. By their nature, digital media are 100% reliably copied, so the need for an effective marking system is obvious. This is where watermarking comes in. Watermarking stands for the embedding of perceptually invisible information into image data that identify the rightful creator/owner. Watermarks should be robust to various image attacks. Every attempt to remove the ownership information from the original image is called an attack. Some common attacks include filtering, JPEG compression, histogram modification, cropping, rotation and downscaling. There are two main directions for embedding, namely the spatial and the frequency domain. The spatial domain techniques are more vulnerable in common image attacks such as filtering or JPEG compression.The frequency-domain approaches are the most popular for image watermarking. In these schemes, the image is being transformed via some common frequency transform and watermarking is achieved by altering the transform coefficients of the image. The transforms that are usually used are the DCT, DFT and the DWT. A question that occurs in such approaches is the number and the position of the altered coefficients in the frequency representation of the image. Many different ideas have been presented, most of them originating from Coxs et al system. Piva et al have extended this idea, thus providing a blind detection system. In all these cases the image is being processed as a whole but the number of coefficients altered is not more than 16000, the usual image size being 512x512. Since most of these processes have a statistical background, we would prefer to use as many coefficients as possible. This is why we suggest the use of subband DCT.In section 2, we present the subband DCT, the decomposition levels and discuss the casting scheme and parameters. In section 3, we test the reading scheme and examine each bands individual contribution in the case of no processing and also the final detection results for five common attacks. We end with the final conclusions in section 2. SUBBAND DCT AND WATERMARK CASTINGJung and Mitra have introduced the subband DCT in 1996. It is a method that involves both wavelets and the Discrete Cosine Transform (DCT). The original image is sub sampled and filtered with the use of a high pass and a low pass filter. The combination of the two filters for each direction (horizontal and vertical) of filtering gives four subbands for each level of decomposition. The band that corresponds to low pass filtering in both directions (LL band) can be further subsampled and filtered thus providing another level of decomposition. Finally, each of the bands is transformed with the use of the DCT.For our experiments, we had to select the number of decomposition levels and the wavelet to be used. We tried different numbers of decomposition levels, namely 1, 2 and 3. Experimental results have shown that there wasnt any significant improvement in the detection results for more levels than one, while at the same time, the image degradation was more easily observed. So we decomposed the original image into one level with four bands. This was accomplished using the simplest wavelet, that is Haar. The next step was to perform a DCT on each of the bands. To cast our watermark we used the following formula:where ti are the transformed coefficients, ti are the watermarked coefficients and xi is a random sequence of Gaussian distribution, used as the watermark. The a- parameter has to do with the strength of the casting. We use two different values for it, one for the LL-band and a different one for all other bands, that is a=0.1 for the LL- band and 0.2 for the others. The reason for this is that the low frequency band is more vulnerable to changes, meaning that slight changes are easily noticeable. The i parameter ranges from 1 to 20000, thus leading in a satisfactory number of 80000 coefficients that are altered. In each band we start from coefficient 5000 in the zig-zag scanning order.Image watermarking using block site selection and DCT domain constraintsAbstract: In this paper we propose an image watermarking algorithm based on constraints in the Discrete Cosine Transform (DCT) domain.An image watermarking algorithm has two stages: signature casting (embedding) and signature detection. In the first stage it embeds an identifying label in the image. This is recognized in the second stage. The proposed algorithm has two processing steps. In the first step certain pixel blocks are selected using a set of parameters while in the second step a DCT coefficient constraint is embedded in the selected blocks. Two different constraint rules are suggested for the parametric modification of the DCT frequency coefficients. The first one embeds a linear constraint among certain selected DCT coefficients and the second defines circular detection regions according to the given parameters. The watermarks cast by the proposed algorithm are resistant to JPEG compression and filtering.1. IntroductionDigital watermarks in the general context of TV broadcasting and cryptology were discussed in. To avoid the unauthorized distribution of images or other multimedia property, various solutions have been proposed. Most of them make unobservable modifications to images, that can be detected afterwards . Such image changes are called watermarks. The watermark should not alter visibly the image and it should be robust to alterations which may be caused by various image processing techniques.Algorithms proposed for watermarking have been reported in various papers. They are either stochastic or deterministic. These algorithms are either in image intensity domain or in frequency domain. In the middle range DCT frequency coefficients from the 8*8 pixel blocks are used for embedding a constraint. In the signature is embedded in the DCT coefficients obtained after applying the DCT transform in the entire image.An watermarking algorithm has two stages: watermarking casting and detection. By means of watermark casting a specific code assigned to the owner is embedded in the image. In the detection stage the algorithm identifies the given code. Signal detection theory is a well-established field with many applications. A watermarked image can be processed by means of various image transformations and processing algorithms which may be able to destroy, intentionally or not, the digital watermark. Image compression is the most likely transformation that an image may undergo. The standard still image compression algorithm is JPEG. JPEG is based on the minimization of the energy in the Discrete Cosine Transform (DCT) domain. In the case of lossy compression, the image suffers information loss in the high frequency domain.In the proposed watermark casting algorithm from, the image is partitioned in 8*8 pixel blocks similar to the JPEG algorithm. The watermarking algorithm consists of two steps. The first step selects certain blocks according to a Gaussian network. In the selected blocks we modify DCT coefficients such that they fulfill a given constraint. The parameters of the Gaussian functions and of the imposed constraints on the DCT coefficients make up the watermark code. In the detection stage we first check for the DCT constraints and afterwards for the respective block location.In Section 2 we propose a technique for choosing block sites. The DCT constraint embedding step is explained in Section 3. The detection stage is presented in Section 4. This analysis is necessary in order to determine the suitable watermark parameters such that each watermark is distinctly identified from all the others. 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