The growth of networked multimedia systems has magnified the need for image copyright protection. One approach used to address this problem is to add an invisible structure to an image that can be used to seal or mark...
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The growth of networked multimedia systems has magnified the need for image copyright protection. One approach used to address this problem is to add an invisible structure to an image that can be used to seal or mark it. These structures are known as digital watermarks. We describe two techniques for the invisible marking of images. We analyze the robustness of the watermarks with respect to linear and nonlinear filtering, and JPEG compression. The results show that our watermarks detect all but the most minute changes to the image.
In ATM networks cell loss causes data to be dropped in the channel. When digital video is transmitted over these networks one must be able to reconstruct the missing data so that the impact of these errors is minimize...
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In ATM networks cell loss causes data to be dropped in the channel. When digital video is transmitted over these networks one must be able to reconstruct the missing data so that the impact of these errors is minimized. In this paper we describe a Bayesian approach to conceal these errors. Assuming that the digital video has been encoded using the MPEG1 or MPEG2 compression scheme, each frame is modeled as a Markov random field. A maximum a posteriori estimate of the missing macroblocks and motion vectors is described based on the model.
This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies' four-tap filter, an original image is decomposed into three detail images and one approximate i...
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This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies' four-tap filter, an original image is decomposed into three detail images and one approximate image. The decomposition can be recursively applied to the approximate image to generate a lower resolution of the pyramid. The segmentation starts at the lowest resolution using the K-means clustering scheme and textural features obtained from various sub-bands. The result of segmentation is propagated through the pyramid to a higher resolution with continuously improving the segmentation. The lower resolution levels help to build the contour of the segmented texture, while higher levels refine the process, and correct possible errors.
We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions...
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We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions to guide the sequential search at higher resolutions. As a consequence, the dependence on a priori knowledge of the image edges is greatly reduced. Estimating the sequential search parameters from lower resolution images provides for a more accurate and less costly search of edge paths in the image.
In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. T...
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In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. The second approach recovers lost macroblocks by minimizing intersample variations within each block and across its boundaries. Moreover, a new technique for packing ATM cells with compressed data is also proposed.
Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of v...
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Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of video data are to be processed, particularly in real-time. We present a new algorithm to reconstruct DC coefficient images of a DCT and motion compensation compressed video sequence, e.g. MPEG. The histograms of the DC coefficient images can be used to detect scene changes.
The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more compl...
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The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more compl...
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The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is through the use of parallel processing. In this paper we address one aspect of the parallel implementation of the JPEG still image compression standard on the MasPar MP-1, a massively parallel SIMD computer. We develop a novel byte alignment algorithm used to efficiently output compressed data from the parallel system.< >
Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maxi...
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Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maximization of the posterior marginals (MPM) criterion for the segmentation operation. A Markov random field (MRF) model is used for the pixel class labels. The authors present experimental results demonstrating the use of the new algorithm on synthetic images and medical imagery.< >
A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to...
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