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IEEE International Conference on image processing

作者： R.B. Wolfgang E.J. Delp Computer Vision and Image Processing Laboratory Purdue Multimedia Testbed Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

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.

关键词： Watermarking Digital images Multimedia systems Copyright protection Seals Robustness Nonlinear filters Filtering Transform coding image coding

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A Bayesian approach to error concealment in encoded video streams

A Bayesian approach to error concealment in encoded video st...

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IEEE International Conference on image processing

作者： P. Salama N. Shroff E.J. Delp Computer Vision and Image Processing Laboratory Purdue Multimedia Testbed Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA Purdue University System West Lafayette IN US

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.

关键词： Bayesian methods Streaming media Intelligent networks Laboratories Markov random fields Video sequences Interpolation image reconstruction Motion estimation computer errors

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Texture segmentation using hierarchical wavelet decomposition

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PATTERN RECOGNITION 1995年第12期28卷 1819-1824页

作者： Salari, E Ling, Z Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Toledo Toledo OH 43606 U.S.A.

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.

关键词： Texture segmentation Wavelet transform Clustering algorithm Multiresolution segmentation

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Multiresolution sequential edge linking

Multiresolution sequential edge linking

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IEEE International Conference on image processing

作者： G.W. Cook E.J. Delp School of Electrical Engineering Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

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.

关键词： Joining processes image edge detection image resolution Spatial resolution Pixel computer vision image processing Signal to noise ratio Technological innovation Laboratories

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Error concealment techniques for encoded video streams

Error concealment techniques for encoded video streams

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IEEE International Conference on image processing

作者： P. Salama N.B. Shroff E.J. Coyle E.J. Delp School of Electrical Engineering Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

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.

关键词： Streaming media Asynchronous transfer mode Decoding Video compression image coding Video sequences computer errors computer vision image processing Laboratories

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A fast algorithm for video parsing using MPEG compressed sequences

A fast algorithm for video parsing using MPEG compressed seq...

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IEEE International Conference on image processing

作者： K. Shen E.J. Delp School of Electrical Engineering Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

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.

关键词： Video compression Transform coding Software libraries image reconstruction Discrete cosine transforms Motion compensation image coding Video sequences Histograms Layout

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AN INVESTIGATION OF JPEG image AND VIDEO COMPRESSION USING PARALLEL processing

AN INVESTIGATION OF JPEG IMAGE AND VIDEO COMPRESSION USING P...

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1994 IEEE International Conference on Acoustics, Speech and Signal processing

作者： COOK, GW DELP, EJ Computer Vision Ond Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN 47907-1285 United States

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. © 1994 IEEE.

关键词： image compression

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An investigation of JPEG image and video compression using parallel processing

An investigation of JPEG image and video compression using p...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： G.W. Cook E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

关键词： Transform coding Video compression Parallel processing image coding image storage Digital images Concurrent computing Parallel algorithms image processing Bandwidth

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Parameter estimation and segmentation of noisy or textured images using the EM algorithm and MPM estimation

Parameter estimation and segmentation of noisy or textured i...

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IEEE International Conference on image processing

作者： M.L. Comer E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

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.< >

关键词： Parameter estimation image segmentation Pixel Markov random fields Probability computer vision image processing Laboratories Tellurium Biomedical imaging

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Analysis of texture images using robust fractal description

Analysis of texture images using robust fractal description

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1995 IEEE Southwest Symposium on image Analysis and Interpretation, IAI 1994

作者： Avadhanam, N. Mitra, S. Center for Image Processing and Integrated Computing Dept. of Electr. and Comput. Eng. California Univ. DavisCA95616 United States Computer Vision and Image Analysis Lab Dept. of Electrical Engineering Texas Tech University LubbockTX79401 United States

ISBN: (纸本)0818662506

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 the lacunarity measure is used to characterize natural textures since fractal dimension alone cannot totally characterize texture images. Segmentation of natural textures is successfully achieved by a k-means clustering algorithm using fractal dimension and the additional measure as representative features. © 1994 IEEE.

关键词： image texture

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