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Cell-broadband-engine-based realtime wavelet decomposition for hdtv video images and beyond

Cell-broadband-engine-based realtime wavelet decomposition f...

引用

IEEE International conference on Multimedia and Expo (ICME 2006)

作者： Asahara, Akihiro Doi, Munehiro Mori, Yumi Nishiyama, Hiroki Nakano, Hiroki IBM Japan Ltd. Japan

ISBN: (纸本)9781424403660

The Cell Broadband Engine (CBE) is a novel multi-core microprocessor designed to provide compact and high-performance processing capabilities for a wide range of applications. Real-time image processing applications with parallelism for large amounts of data are good examples to demonstrate the unique capabilities of the CBE. In this paper, we describe the evaluation of the performance for image processing using wavelet transforms on CBE. Our results show that the CBE is extremely efficient in this processing compared with commercially available processors, and thus, we conclude that the CBE is quite suitable for next generation large pixel formats, such as 4K/2K-Digital Cinema.

关键词： image compression

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Real-time image wavelet coding for low bit rate transmission

Real-time image wavelet coding for low bit rate transmission

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International conference on signal processing and Multimedia applications

作者： Luo, Gaoyong Buckinghamshire Chilterns Univ Coll Fac Technol High Wycombe HP11 2JZ Bucks England

ISBN: (纸本)9728865643

Embedded coding for progressive image transmission has recently gained popularity in image compression community. However, current progressive wavelet-based image coders tend to be complex and computationally intense requiring large memory space. The encoding process usually sends information on the lowest-frequency wavelet coefficients first. At very low bit rates, images compressed are therefore dominated by low frequency information, where high frequency components belonging to edges are lost leading to blurring the signal features. This paper presents a new image coder for real-time transmission, employing edge preservation based on local variance analysis to improve the visual appearance and recognizability of compressed images. The analysis and compression is performed by dividing an image into blocks. Lifting wavelet filter bank is constructed for image decomposition and reconstruction with the advantages of being computationally efficient and boundary effects minimized. A modified SPIHT algorithm with more bits used to encode the wavelet coefficients and transmitting fewer bits in the sorting pass for performance improvement, is used to reduce the correlation of the coefficients at scalable bit rates. Local variance estimation and edge strength measurement can effectively determine the best bit allocation for each block to preserve the local features. Experimental results demonstrate that the method performs well both visually and in terms of quantitative performance measures, and offers error resilience feature that is evaluated using a simulated transmission channel with random error.

关键词： image embedded coding edge preservation local variance analysis bit rate allocation error resilience

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signal denoising based on parametric Haar-like transforms

Signal denoising based on parametric Haar-like transforms

引用

International conference on signal processing and Multimedia applications

作者： Minasyan, Susanna Egiazarian, Karen Astola, Jaakko Guevorkian, David Tampere Univ Technol FIN-33101 Tampere Finland Nokia Res Ctr Tampere Finland

ISBN: (纸本)9728865643

Orthogonal transforms have found considerable interest in signal denoising applications. Recently Parametric Haar-like Transforms (PHTs) have been introduced and shown to be efficient in image denoising and compression applications. PHT is such that it may be computed with fast algorithm in structure a similar to that of classical fast Haar transform and such that its matrix contains a predefined basis vector, called generating vector, as its first row. PHT may be adapted to the characteristics of the input signal or to its parts by a proper selection of the generating vectors. Possibility of adaptation to the input signal may, in principle, be significant source for performance improvement of transform based signal processing algorithms. In this paper, the capability of parametric Haar-like transforms, in 1-D signal denoising application is explored. A new PHT based post-processing algorithm for 1-D signal denoising is proposed, which may be combined with another denoising method in order to improve the quality of the output signal. Experiments were conducted where the basic wavelet thresholding based signal denoising method was complemented with the proposed post-processing algorithm. Simulation results illustrate significant performance improvement due to the use of the proposed algorithm.

关键词： signal denoising wavelet threshold parametric transform

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The application of image compression based on discrete wavelet transform

The application of image compression based on discrete wavel...

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International Computer conference on wavelet Active Media Technology and Information processing

作者： Liu, Dan Li, Jianping Gu, Xiaofeng Liao, Jianming Zhan, Siyu Univ Elect Sci & Technol China Sch Comp Sci Int Ctr Wavelet Anal & Its Applicat Chengdu 610054 Peoples R China Logistical Engn Univ Chongqing 400016 Peoples R China

ISBN: (纸本)9812700420

The discrete wavelet analysis has become the up-to-date technology for signal processing, especially for image compression. The effect to image compression has been testified by all kinds of applications and researches. Discrete wavelet transform (DWT) represents image as a(1) sum of wavelets on the different resolution levels. Basis for wavelet transform can be composed of any function that satisfies the requirements of multiresolution analysis. It is clear that there exits a numerous selection of wavelet families in according to the choice of wavelet function. The choice of wavelet family depends on the applications. This choice in image compression application must depend on image content. In this paper, we will introduce fundamentals of wavelet based image compression. The results of image quality for different wavelet functions, compression ratios, image contents and resolution are given. So we can find comparatively better way to compress image according to the different requirements.

关键词： DWT image compression multiresolution analysis PSNR

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Efficient, highly scalable wavelet image coding for network applications

Efficient, highly scalable wavelet image coding for network ...

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4th International conference on Communications, Circuits and Systems (ICCCAS 2006)

作者： Gan, Tao Zhou, Nan Zhu, Weile UESTC Sch Elect Engn Si Chuan Peoples R China

ISBN: (纸本)0780395840

A new efficient, highly scalable wavelet image coding algorithm is proposed in this paper. Two techniques-morphological representation and quadtree partitioning - are efficiently combined to exploit the nature of wavelet coefficients. Thanks to the list structure, the new coding algorithm achieves fine fractional bit-plane coding with negligible additional complexity. Experiments show that it performs comparable or better than the state-of-the-art codecs. Furthermore, the flexible codec supports both quality and resolution scalability, which is very attractive in many network applications.

关键词： image coding Scalability Clustering algorithms Partitioning algorithms Codecs image resolution wavelet coefficients Decoding Gallium nitride IP networks

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A model-based approach to correlation estimation in wavelet-based distributed source coding with application to hyperspectral imagery

A model-based approach to correlation estimation in wavelet-...

引用

IEEE International conference on image processing (ICIP 2006)

作者： Cheung, Ngai-Man Ortega, Antonio Univ So Calif Inst Signal & Image Proc Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)9781424404810

In many practical distributed source coding (DSC) applications correlation information has to be obtained at the encoder in order to determine the encoding rate. Coding efficiency depends strongly on the accuracy of this correlation estimation, which often has to be performed under rate and complexity constraints. In this paper we focus on correlation estimation for wavelet-based DSC. We extend our previously proposed model-based estimation techniques, which provided accurate estimates of bit-plane level correlation under rate constraints, in the simple case where bit-planes are generated from the binary representation of the sources. To extend the model-based approach to wavelet-based DSC, we need to address two issues. Firstly, in order to improve coding efficiency, bit-planes are typically generated by more sophisticated algorithms in wavelet-based DSC (e.g., by deciding on the bitplane scan order based on coefficient "significance"), which makes model-based estimation more challenging. Secondly, certain wavelet subbands may not have enough coefficients for reliable model estimation, so that model-based techniques alone may not be sufficiently accurate. We propose solutions to these problems and, using a DSC-based hyperspectral image system as example, we demonstrate that model-based estimation can lead to efficient system implementation with lower computational and data exchange requirements, and improved parallelism, while incurring only small degradation in coding efficiency.

关键词： distributed source coding Slepian-Wolf correlation estimation hyperspectral image

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A dynamic programming approach to distortion-energy optimization for distributed wavelet compression with applications to data gathering in wireless sensor networks

A dynamic programming approach to distortion-energy optimiza...

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31st IEEE International conference on Acoustics, Speech and signal processing

作者： Ciancio, Alexandre Ortega, Antonio Univ So Calif Inst Signal & Image Proc Los Angeles CA 90089 USA

ISBN: (纸本)9781424404681

We address a scenario where energy-constrained sensors in a wireless sensor network can choose among different distributed coding schemes to encode their data. We propose a framework where the network is described as a graph, with sensors representing the nodes, and where communication and processing costs are associated to edge weights and the coding schemes associated to states of operation. After describing data transitions and edge costs, we show that a shortest-path algorithm can be used to find the optimum network configuration, i.e., the one that leads to the lowest overall energy consumption.

关键词： Optimization

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wavelet-based pavement distress detection and evaluation

Wavelet-based pavement distress detection and evaluation

引用

wavelets - applications in signal and image processing X conference

作者： Zhou, J Huang, PS Chiang, FP SUNY Stony Brook Dept Mech Engn Stony Brook NY 11794 USA

ISBN: (纸本)0819450804

An automated pavement inspection system consists of image acquisition and distress image processing. The former is accomplished with imaging sensors, such as video cameras and photomultiplier tubes. The latter includes distress detection, isolation, classification, evaluation, segmentation, and compression. We focus on wavelet-based distress detection, isolation, and evaluation. After a pavement image is decomposed into different-frequency subbands by the wavelet transform, distresses are transformed into high-amplitude wavelet coefficients and noise is transformed into low-amplitude wavelet coefficients, both in the high-frequency subbands, referred to as details. Background is transformed into wavelet coefficients in a low-frequency subband, referred to as approximation. First, several statistical criteria are developed for distress detection and isolation, which include the high-amplitude wavelet coefficient percentage (HAWCP), the high-frequency energy percentage (HFEP), and the standard deviation (STD). These criteria are tested on hundreds of pavement images differing by type, severity, and extent of distress. Experimental results demonstrate that the proposed criteria are reliable for distress detection and isolation and that real-time distress detection and screening is currently feasible. A norm for pavement distress quantification, which is defined as the product of HAWCP and HFEP, is also proposed. Experimental results show that the norm is a useful index for pavement distress evaluation. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

关键词： wavelet transform automated pavement inspection pavement distress image processing distress detection and isolation distress evaluation

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applications of non-orthogonal filter banks to signal and image analysis

Applications of non-orthogonal filter banks to signal and im...

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IEEE/PES Transmission and Distribution conference and Exposition Latin America

作者： Soares, Luciana R. de Oliveira, H. M. Cintra, Renato J. S. Univ Fed Pernambuco Dept Elect & Syst Signal Proc Grp CP 7800 BR-50711970 Recife PE Brazil Univ Fed Pernambuco Dept Stat Recife PE Brazil

ISBN: (纸本)9781424402878

A non-orthogonal wavel ET-based multiresolution analysis was already provided by scaling and wavelet filters derived from Gegenbauer polynomials. Allowing for odd n (the polynomial order) and a value (a polynomial parameter) within the orthogonality range of such polynomials, scaling and wavelet functions are generated by frequency selective FIR filters. These filters have compact support and generalized linear phase. Special cases of such filter banks include Haar, Legendre, and Chebyshev wavelets. As an improvement, it has been achieved that for specific a values it is possible to reach a filter with flat magnitude frequency response. We obtain a unique closed expression for a value for every n odd value. The main advantages in favor of Gegenbauer filters are their smaller computational effort and a constant group delay, as they are symmetric filters. Potential applications of such wavelets include fault analysis in transmission lines of power systems and image processing.

关键词： chebyshev wavelets discrete-time filters filter banks Gegenbauer polynomials Gegenbauer wavelets image analysis legendre wavelets multiresolution analysis signal analysis wavelet transform

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Lighting inhomogeneities removal by wavelet analysis

Lighting inhomogeneities removal by wavelet analysis

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conference on wavelet applications in Industrial processing IV

作者： Laligant, O. Meriaudeau, F. Truchetet, F. CNRS Le2i UMR 5158 12 Rue Fonderie Le Creusot France

ISBN: (纸本)9780819464811

Lighting uniformity is always an issue in visual inspection of industrial parts. While the human visual system is quite able to cope with this kind of problem, artificial vision systems are subject to false and no detection rate increase when the lighting conditions are not well mastered. If many authors have proposed various methods to unbiase image, most of the time they are designed in an "ad hoc" way and they are very dependent on the experimental conditions. It can be shown that a large class of the inhomogeneities in images due to lighting conditions can be reasonably modelled by a polynomial dependency of the luminance. The wavelet analysis theory proposes a lot of bases with various number of vanishing moments. By keeping only some wavelet coeffcients it is possible to reconstruct an unbiased signal in which the interesting features, characterized by there resolution pertinence range, are cleaned from the polynomial variations supposed to be due to inhomogeneous lighting conditions. In this paper, after a brief presentation of a realistic lighting model, we show that the luminance image can be approximated by a polynomial function. Then we propose a method, based on a partial reconstruction after multiresolution analysis, allowing to remove approximately the polynomial component of the signal. Two variants are also proposed to improve the performance by either detecting more precisely the polynomial component, either limiting the error occurring when neglecting the approximation signal in the reconstruction process. A simulation in 1D and 2D illustrates these propositions. Some results obtained on examples of real artificial vision inspection problems are finally given.

关键词： artificial vision surface inspection lighting homogeneity wavelets vanishing moments wavelet filtering

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