In ATM networks cell loss or channel errors can cause 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 the...
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In ATM networks cell loss or channel errors can cause 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 concealing these errors by post-processing the received data. In a previous paper (see IEEE Proc. Int. Conf. on imageprocessing p.49-52, 1996), each frame in the sequence was modeled as a Markov random field, and maximum a posteriori estimates of the missing macroblocks were obtained. However, the maximum a posteriori estimate is not unique, and the algorithm is also computationally intensive. In this paper we demonstrate, that by using median filtering we arrive at a suboptimal estimate. This will allow real-time nearly optimal reconstruction of the missing data.
We present a parallel implementation of an MPEG encoder on the Intel Paragon supercomputer. In our approach, both spatial and temporal parallelism have been exploited, While the Paragon has the computation capacity to...
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In this paper we present new results relative to the "expectation-maximization/maximization of the posterior marginals" (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured i...
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In this paper we present new results relative to the "expectation-maximization/maximization of the posterior marginals" (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured images. The goal of the EM/MPM algorithm is to minimize the expected value of the number of misclassified pixels. We present new theoretical results in this paper which show that the algorithm can be expected to achieve this goal, to the extent that the EM estimates of the model parameters are close to the true values of the model parameters. We also present new experimental results demonstrating the performance of the algorithm.
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 this paper, we present a new system to segment and label CT brain slices using a self-organizing Kohonen network. Our aim is to extract reliable and robust measures from CT images of Traumatic Brain Injury (TBI) pa...
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In this paper, we present a new system to segment and label CT brain slices using a self-organizing Kohonen network. Our aim is to extract reliable and robust measures from CT images of Traumatic Brain Injury (TBI) patients that can accurately describe the morphological changes in the brain as recovery progresses. Segmentation is performed by assigning a feature pattern to each voxel, consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is input to Kohonen network for an unsupervised classification of the voxels into regions.
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.
We present a control scheme for a rate scalable video codec. We describe a wavelet based video codec with motion compensation used to reduce temporal redundancy. The prediction error frames are encoded using an embedd...
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We present a control scheme for a rate scalable video codec. We describe a wavelet based video codec with motion compensation used to reduce temporal redundancy. The prediction error frames are encoded using an embedded zerotree wavelet (EZW) approach which allows data rate scalability. Since motion compensation is used in the algorithm, the duality of the decoded video may decay due to the propagation of errors in the temporal domain. An adaptive motion compensation scheme is proposed to address this problem. We show that using our control scheme the quality of the decoded video can be maintained at any data rate.
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.
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.
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