This paper addresses the problem of estimating, analyzing and tracking objects moving with spatio-temporal rotational motion (spin or orbit). It is assumed that the digital signals of interest are acquired from a came...
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The growth of networked multimedia systems has complicated copyright enforcement relative to digital images. One way to protect the copyright of digital images is to add an invisible structure to the image (known as a...
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The growth of networked multimedia systems has complicated copyright enforcement relative to digital images. One way to protect the copyright of digital images is to add an invisible structure to the image (known as a digital watermark) to identify the owner. In particular, it is important for Internet and image database applications that as much of the watermark as possible remain in the image after compression. image adaptive watermarks are particularly resistant to removal by signalprocessing attacks such as filtering or compression. Common image adaptive watermarks operate in the transform domain (DCT or wavelet);the same domains are also used for popular image compression techniques (JPEG, EZW). This paper investigates whether matching the watermarking domain to the compression transform domain will make the watermark more robust to compression.
In this paper, we address the problem of lossless and nearly-lossless multispectral compression of remote-sensing data acquired using SPOT satellites. Lossless compression algorithms classically have two stages: Trans...
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ISBN:
(纸本)0819427446
In this paper, we address the problem of lossless and nearly-lossless multispectral compression of remote-sensing data acquired using SPOT satellites. Lossless compression algorithms classically have two stages: Transformation of the available data, and coding. The purpose of the first stage is to express the data as uncorrelated data in an optimal way. In the second stage, coding is performed by means of an arithmetic coder. In this paper, we discuss two well-known approaches for spatial as well as multispectral compression of SPOT images: 1) The efficiency of several predictive techniques (MAP, CALIC, 3D predictors), are compared, and the advantages of 2D versus 3D error feedback and context modeling are examinated;2) The use of wavelet transforms for lossless multispectral compression are discussed. Then, applications of the above mentionned methods for quincunx sampling are evaluated. Lastly, some results, on how predictive and wavelet techniques behave when nearly-lossless compression is needed, are given.
We introduce a continuous scare wavelet detector for identifying masses (possible breast cancers) in mammograms. Continuous-scale wavelet algorithms have been discussed in the past, however this is the first reported ...
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ISBN:
(纸本)081942840X
We introduce a continuous scare wavelet detector for identifying masses (possible breast cancers) in mammograms. Continuous-scale wavelet algorithms have been discussed in the past, however this is the first reported algorithm that uses a scaled version of the same mother wavelet at each scare of analysis. This single mother wavelet property leads to a simpler implementation and a more direct application of detection theory to recognition problems than traditional multiscale analysis. In addition, we show that a continuous-scale search is necessary for computer aided diagnosis of mammography since traditional solutions using dyadic scales (powers of two) either fail to detect some masses or signal too many false alarms. Our novel wavelet detector combines a wavelet formulation with the classical theory of constant false alarm rates (C-FAR) detectors. Finally, we show that our algorithm is able to detect masses in actual mammograms that could not be seen using conventional windowing and leveling of other traditional methods of contrast enhancement.
The principle of Perception Redundancy Reduction (PRR) states that by optimally balancing between the information reduction of the input data and sufficient redundancy, classification performance should improve due to...
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ISBN:
(纸本)081942840X
The principle of Perception Redundancy Reduction (PRR) states that by optimally balancing between the information reduction of the input data and sufficient redundancy, classification performance should improve due to smaller search space from the reduced dimensions and noise-invariant from retained redundancy. For dimensionality reduction using global information, Principal Component Analysis (PCA) is a well suited method especially for signalprocessing task. However, for pattern classification purpose and for image classification in particular, operating on raw input data sometimes limits the benefit of the PCA. Following the Expansion-Reduction model of data-processing, we propose the use of Multiple Resolution Analysis (MRA) through continuous wavelet Transform (WT) to rearrange input data into different combinations according to wavelet kernel criteria. Quantization further provides intrinsic de-noising result plus sparseness in the transform space which preconditions the orthogonality. PCA is then performed on each level of the data resolution, generating mutually supportive classification discriminants. All together, this multiple resolution Principal wavelet Component (PWC) method provides two significant advantages over traditional PCA: i) Providing integrated de-noising and re-distribution of information content, thereby establishes controlled and mathematically sound downsampling scheme, which alleviates the curse of dimensionality and, at the same time, attenuates noises, ii) Establishing a multiple resolution decision process, whereas each resolution level provides supplemental principal wavelet components, being at least quasi-orthogonal by nature, to support classification with maximum tolerance.
The proceedings contains 179 papers from the 1997 31st ASILOMAR conference. Topics discussed include: adaptive nonlinear filters;resource allocation in wireless networks;speech and audio coding;communications over fad...
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The proceedings contains 179 papers from the 1997 31st ASILOMAR conference. Topics discussed include: adaptive nonlinear filters;resource allocation in wireless networks;speech and audio coding;communications over fading channels;adaptive and nonlinear methods in wavelet-based processing;performance evaluation for nonlinear and adaptive systems;mobile communications;advanced techniques for wireless communications;compression and signalprocessingapplications;radar and sonars;biometric identification;image/video compression and transmission, and protocol issues for the Internet;field programmable gate arrays (FPGA) and applications;non-Gaussian signalprocessing;and network access technologies.
We address multiresolutional encoding and decoding within the embedded zerotree wavelet (EZW) framework for both images and video. By varying a resolution parameter, one can obtain decoded images at different resoluti...
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The emergence of fast, embeddable parallel processors such as SIMD meshes and networked multiprocessors has motivated increased parallel algorithm development for image and signalprocessing (ISP) and automated target...
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ISBN:
(纸本)0819429112
The emergence of fast, embeddable parallel processors such as SIMD meshes and networked multiprocessors has motivated increased parallel algorithm development for image and signalprocessing (ISP) and automated target recognition (ATR). Among such applications are real-time video compression for Internet communication, videotelephony, and videoteleconferencing. In general, image or signal compression transforms tend to be attractive candidates for parallel implementation. For example, due to a rectangular, non-overlapping partition structure, block-oriented transforms such as JPEG can be processed in pipeline fashion. In contrast, implementational challenges accrue as a result of between-brock data and control dependencies encountered in various pyramid-structured or hierarchical compression transforms such as wavelet-based coding. This paper summarizes ongoing research in the mapping of image compression transforms to SIMD-parallel computers. Three classes of algorithms are considered: (I) streaming, (2) block-oriented, and (3) hierarchically structured. It is shown that Classes 1 and 2 are suitable for SIMD computation, particularly where mesh segments can be connected to form a pipeline. Computation is facilitated by modifying a SIMD mesh to form a brute-force synchronous MIMD processor, which is called a multi-SIMD or MSIMD architecture. Several designs for pipelined compression transform implementation on an MSIMD mesh are analyzed in terms of critical computational complexity and error. Analysis also emphasizes theory, software, and parallelism required to support resolution of data and control dependencies encountered in ISP/ATR practice.
A new implementation of the Discrete wavelet Transform is presented for applications such as image restoration and enhancement. It employs a dual tree of wavelet filters to obtain the real and imaginary parts of the c...
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A new implementation of the Discrete wavelet Transform is presented for applications such as image restoration and enhancement. It employs a dual tree of wavelet filters to obtain the real and imaginary parts of the complex wavelet coefficients. This introduces limited redundancy (4 : 1 for 2-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency. We show how the dual-tree complex wavelet transform can provide a good basis for multi-resolution image denoising and de-blurring.
A family of discrete-time linear-phase nearly orthogonal wavelet banks is introduced. These wavelet banks are intermediate cases between orthogonal wavelet banks having nonlinear-phase impulse responses and biorthogon...
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A family of discrete-time linear-phase nearly orthogonal wavelet banks is introduced. These wavelet banks are intermediate cases between orthogonal wavelet banks having nonlinear-phase impulse responses and biorthogonal banks having linear-phase impulse responses. For these banks, the wavelet and scaling functions are made very regular and the wavelet function has several vanishing moments. Strightly speaking, the proposed filter banks are not real wavelet banks in the sense that there are negligible aliased terms and a very small reconstruction error for the unaliased component. Several examples are included showing the usefulness of the proposed banks in signalprocessingapplications.
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