The huge development of new technologies and the apparition of more and more sophisticated open communication system creates a new challenge to protect digital content from piracy. Digital watermarking is a research a...
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The huge development of new technologies and the apparition of more and more sophisticated open communication system creates a new challenge to protect digital content from piracy. Digital watermarking is a research axis and a new technique suggested as a solution to these problems. This technique consists of inserting an identification information (watermark) into digital data (audio, video, image, databases...) in an invisible and indelible manner and in such a way not to degrade original medium's quality. Moreover, we must be able to correctly extract the watermark despite the deterioration of the watermarked medium (i.e. attacks). In this paper we propose a system for watermarking satellite images. We chose to embed the watermark into frequency domain, precisely the discrete wavelet transform (DWT). We applied our algorithm on satellite images of Tunisian center. The experiments show satisfying results. In addition, our algorithm showed an important resistance facing different attacks, notably the compression (JPEG, JPEG2000), the filtering, the histogram's manipulation and geometric distortions such as rotation, cropping, and scaling
The industry standard joint photographers expert group (JPEG) compression can lead to noticeable 'blocking artifacts' in many cases. High frequency details of the coded images are mainly contaminated by quanti...
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The industry standard joint photographers expert group (JPEG) compression can lead to noticeable 'blocking artifacts' in many cases. High frequency details of the coded images are mainly contaminated by quantization noise. The deblocking approach of JPEG compressed images using overcomplete wavelet representation can be improved by preserving the image details and reducing the effect of quantization noise as much as possible. An estimation of the actual pixel is obtained from the decoded image. The edge information is extracted from this estimated image by exploiting the cross-scale correlations among the wavelet coefficients and is protected, while the blocking effects in the smooth background regions are smoothed out in the wavelet domain without much blurring. A better improvement in visual quality is achieved if dual tree complex wavelet filters are used instead of the dyadic discrete wavelet transform
In this paper, we have presented our work on the adaptive modeling of quantization process at macro block layer of MPEG encoders. The difficulty of this modeling problem lies in two aspects: 1) the highly nonlinear na...
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ISBN:
(纸本)0780336453
In this paper, we have presented our work on the adaptive modeling of quantization process at macro block layer of MPEG encoders. The difficulty of this modeling problem lies in two aspects: 1) the highly nonlinear nature of the relation between the quantization level and the corresponding number of bits; and 2) the nonstationaryness inherent to most of the practical video signals. We deal with the first aspect of the difficulty by using binary tree (B-tree) fuzzy interpolation algorithm for data approximation problems. The B-tree algorithm turns complicated high dimensional fuzzy decision making process into series of one dimensional fuzzy interpolations in a hierarchical manner. The difficulty of the nonstationaryness is dealt with by online adaptation which adjusts the parameters of membership functions according to domain data. Our experimental results have shown that the adaptive model has better performance than its non-adaptive counterpart as well as the lookup table method widely used and reported in the literature, which suggests that improvements can be well expected if the model is applied to the design of quantization control schemes for MPEG encoders.
Classic image features were once widely used in image classification but have been almost entirely replaced by neural networks today. While the performance of neural networks, especially convolutional neural networks ...
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ISBN:
(数字)9798350352214
ISBN:
(纸本)9798350352221
Classic image features were once widely used in image classification but have been almost entirely replaced by neural networks today. While the performance of neural networks, especially convolutional neural networks (CNNs), is indisputable, their lack of interpretability has become a significant limitation in recent years. This paper explores the effective combination of classic image features and convolutional image features, investigating their differences and similarities. Through a series of experiments, a method is proposed to effectively integrate these two types of features by employing a multiplicative attention mechanism. This approach combines standardized MPEG-7 descriptors with convolutional features before feeding them into the fully connected layer for classification. The final model demonstrates an improvement in classification accuracy and indicates the potential of learning traditional image features from the integrated features.
Blocking effect is the major drawback in DCT-based (discrete cosine transformation) codecs at low bit-rates. In this paper, a post-processing filter is proposed in DCT frequency domain. The proposed algorithm uses a s...
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Blocking effect is the major drawback in DCT-based (discrete cosine transformation) codecs at low bit-rates. In this paper, a post-processing filter is proposed in DCT frequency domain. The proposed algorithm uses a shift block within four adjacent DCT blocks to reduce computational complexity. By slightly modifying several DCT coefficients in the shift block, the artifacts that result from quantization and dequantization process are alleviated. The simulation results show that both visual perception and objective image quality are improved noticeably.
On continuous media transmission using compression techniques, a variable bit rate transmission method is required to maintain the video frame rate at a constant. At the same time, user's Quality of Service must b...
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On continuous media transmission using compression techniques, a variable bit rate transmission method is required to maintain the video frame rate at a constant. At the same time, user's Quality of Service must be guaranteed even if packet loss and delay occur by CPU loads on the client or server, and network traffic increase. In this paper, two variable bit rate transmission methods are described when MPEG compressed video are used. We also introduce both a packet rate control method to reduce the packet loss, and frame rate control method to maintain the frame rate constant under dynamic load conditions. We implemented a prototyped Packet Audio/Video System (PAVS) to evaluate performance of these rate control functions. Through the performance evaluation our PAVS performance has demonstrated the usefulness of our suggested control methods.
In image watermarking, holography usage is a very novel approach. Holography, in fact, is a method to store three-dimensional (3-D) information of an object, however, many of its properties make it very applicable in ...
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In image watermarking, holography usage is a very novel approach. Holography, in fact, is a method to store three-dimensional (3-D) information of an object, however, many of its properties make it very applicable in use of watermarking. In this work, a new blind image watermarking approach is proposed, which embeds a hologram as the watermark into a host image. Moreover, the robustness of the method is examined against some attacks like, JPEG compression, noise addition and cropping
The work presents a robust rate control algorithm for JPEG compression, mainly used in digital cameras. The overall control is based on the statistical properties of JPEG compressed images, the relationship between th...
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The work presents a robust rate control algorithm for JPEG compression, mainly used in digital cameras. The overall control is based on the statistical properties of JPEG compressed images, the relationship between the coding bit rate and the percentage of zeros among the quantized transform coefficients. It allows a good trade off between resources and precision to be obtained.
In this paper the application of a transform coding technique, based on overcomplete independent component analysis (ICA), for the compression of single look intensity synthetic aperture radar (SAR) images is explored...
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In this paper the application of a transform coding technique, based on overcomplete independent component analysis (ICA), for the compression of single look intensity synthetic aperture radar (SAR) images is explored. The method has the advantage of representing the image through almost statistically independent coefficients, with an assigned distribution, so that a scalar entropy constrained quantizer, optimized for the coefficients statistics, can be used. Numerical results on ERS-1 data are presented.
Current steganalytic classifiers always need a large number of cover-stego image pairs for training. However in this paper we focus on a scenario where steganalysts have a few cover-stego image pairs in hand. Meanwhil...
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Current steganalytic classifiers always need a large number of cover-stego image pairs for training. However in this paper we focus on a scenario where steganalysts have a few cover-stego image pairs in hand. Meanwhile steganalysts have no knowledge of the embedding algorithm, and cannot generate corresponding stego images after collecting additional cover images. Hence in this scenario steganalysts cannot match more cover-stego image pairs to augment the training set. To address this issue, we propose a stego feature simulation method to artificially generate cover-stego feature pairs for training. First, we design a cover-stego feature difference model to build the relationship between cover and stego features in pairs. Then, we estimate the model parameters from a few existing cover-stego image pairs in hand. Finally, after extracting steganalytic features from additionally collected cover images, we simulate corresponding stego features with the cover-stego feature difference model to match artificial feature pairs. The experimental results demonstrate that our method can effectively mitigate the shortage of training image pairs by adding adequate artificial feature pairs into training.
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