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检索条件"主题词=Transform coding"

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Block predictive transform coding of still images

Block predictive transform coding of still images

引用

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

作者： Jianzhong Huang S. Liu School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA Hewlett Packard Laboratories Palo Alto CA USA

This paper presents a new DCT based still image coding scheme using block prediction. Unlike a traditional transform coder where subimage blocks of the image are independently coded, the proposed scheme uses a block matching predictor which finds the best match (based on a error criterion) in a search window that consists of a previously coded image region. In this coding scheme, the block predictor is first used to find a prediction vector representing the relative location of the subimage in the search window having similar pixel values as the current subimage, then the differential error residual of the current and predicted subimages is compressed using DCT coding. The quantized DCT coefficients along with the prediction vectors are transmitted or stored for reconstruction by the decoder. This paper develops this coding technique and compares the performance with traditional DCT coding of images.< >

关键词： transform coding Discrete cosine transforms Image coding Codecs Image reconstruction Decoding Motion estimation Compaction Pixel Predictive coding

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An optimization approach for removing blocking effects in transform coding

An optimization approach for removing blocking effects in tr...

引用

Data Compression Conference (DCC)

作者： S. Minami A. Zakhor Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

Summary form only given. This paper proposes a new approach which can be applied to conventional transform coding without introducing additional information or significant blurring. It exploits the correlation between intensity values of boundary pixels of two neighboring blocks. Specifically, it is based on the theoretical and empirical observation that under mild assumptions, quantization of transform coefficients of two neighboring blocks increases the mean squared difference (MSD) between neighboring pixels on their boundaries by an amount dependent upon the width of quantization intervals of the transform coefficients. Therefore, among all permissible inverse quantized coefficients, the set which minimizes this MSD is most likely to reduce the blocking effect. To estimate the set of unquantized coefficients, a constrained quadratic programming problem is solved in which the quantization decision intervals provide upper and lower bound constraints on the coefficients. Computer simulations are used to evaluate the performance of the proposed technique for the 256*256 image known as Lena.< >

关键词： transform coding Quantization Filtering Video compression Image restoration Low pass filters Quadratic programming Computer simulation Discrete cosine transforms Pixel

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Multiple description transform coding of images

Multiple description transform coding of images

引用

IEEE International Conference on Image Processing

作者： V.K. Goyal J. Kovacevic R. Arean M. Vetterli University of California Berkeley CA USA Bell Laboratories Murray Hill NJ USA École Polytéchnique Fédérale de Lausanne Lausanne Switzerland

Generalized multiple description coding (GMDC) is source coding for multiple channels such that a decoder which receives an arbitrary subset of the channels may produce a useful reconstruction. This paper reports on applications of two recently proposed methods for GMDC to image coding. The first produces statistically correlated streams such that lost streams can be estimated from the received data. The second uses quantized frame expansions and hence is conceptually similar to block channel coding, except it is done prior to quantization.

关键词： transform coding Image reconstruction Delay Streaming media Propagation losses Source coding Decoding Image coding Channel coding Quantization

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Interpolative, predictive and pyramid transform coding of color images

Interpolative, predictive and pyramid transform coding of co...

引用

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

作者： B.G. Haskell AT&T Bell Lab. Holmdel NJ USA

Three methods are investigated for improving the image quality obtainable by transform coding at relatively low bit rates. Coefficients are transmitted in the so-called zig-zag scanning order, which approximates an ordering according to increasing spatial frequency. For most blocks, coefficients higher than a certain order all have zero quantized value. These are not sent. Instead an end-of-block word is transmitted to indicate to the receiver that the remaining quantized coefficients of that block were zero. Interpolative transform coding requires side information, whereas predictive transform coding does not. Pyramid transform coding performs the best, but at the expense of considerable additional signal processing.< >

关键词： transform coding Color Vector quantization Image coding Discrete cosine transforms Decoding Frequency Image quality Signal processing Distortion

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Perceptual transform coding with channel error control

Perceptual transform coding with channel error control

引用

IEEE International Conference on Communications (ICC)

作者： N. Guo E. Eberlein H. Gerhauser D. Seitzer Fraunhofer Institute of Integrated Circuits and Systems Erlangen Germany University of Erlangen Erlangen Germany

Error control problems of a perceptual entropy-coded transform coding algorithm for high quality digital audio at low bit rate are considered. Some new methods for reducing the effects of transmission errors on the reconstructed signal are proposed. The methods require very low additional redundancy compared with error-correcting codes (e.g., BCH codes). The results show that the proposed methods achieve significant improvements.< >

关键词： transform coding Error correction Decoding Protection Error correction codes Frequency domain analysis Quantization Entropy coding Acoustic noise Frequency synchronization

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Optimizing wavelet transform coding using a neural network

Optimizing wavelet transform coding using a neural network

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International Conference on Information, Communications and Signal Processing

作者： K. Fanghanel R. Hein K. Kollmann H.C. Zeidler Universitat der Bundeswehr Hamburg Hamburg Germany

Artificial neural nets have become very popular in various applications like pattern recognition, system identification and adaptive control. In general, a neural net is a nonlinear mapping device for function approximation in such a way that the arising error has to be minimized. This leads to an optimization problem where the cost function can be learned instead of being represented by a theoretical model. For that reason we have to discover the essential characteristics of the function to find its representation with minimal redundancy. Considering data compression there are similar requirements which have to be met. In this perspective, feature extraction as a basic capability of neural nets has to be performed for optimizing data compression. We consider wavelet transform coding because of its good fitting properties in both the time and frequency domains. Therefore, the choice of the wavelet is significant for a good fit of the signal and leads to an optimization problem which can be solved by a neural net.

关键词： transform coding Neural networks Artificial neural networks Data compression Pattern recognition System identification Adaptive control Function approximation Cost function Redundancy

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The LOT: a link between block transform coding and multirate filter banks

The LOT: a link between block transform coding and multirate...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： H.S. Malvar Department of Electrical Engineering University of Brasilia Brasilia Brazil

The lapped orthogonal transform (LOT) is a novel transform for block signal processing with overlapping basis functions. The LOT can also be viewed as an efficient quadrature-mirror-filter bank in which the analysis and synthesis filters have identical FIR (finite-impulse-response) responses. The author shows that the LOT filter bank leads to perfect signal reconstruction with a relative low level of spectral images. The main advantages of the LOT filter bank are its short filter lengths (twice the number of bands) and its fast algorithm, based on the fast discrete cosine transform.< >

关键词： transform coding Channel bank filters Filter bank Finite impulse response filter Matrices Discrete cosine transforms Signal synthesis Image coding Image reconstruction Delay

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Terrain-adaptive transform coding of multispectral data

Terrain-adaptive transform coding of multispectral data

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： J.A. Saghri A.C. Tescher J.T. Reagan Lockheed Palo Alto Research Labaratory Palo Alto CA USA

Presents a robust and implementable compression algorithm for multispectral imagery with selectable quality level within the near-lossless to visually lossy range. The three-dimensional terrain-adaptive transform-based algorithm involves a one dimensional Karhunen-Loeve transform (KLT) followed by two-dimensional discrete cosine transform (DCT). The images are spectrally decorrelated via the KLT to produce the eigen images. The resulting spectrally decorrelated eigen images are then compressed using the JPEG algorithm. The key feature of this approach is that it incorporates the best methods available to fully exploit the spectral and spatial correlation in the data. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral decorrelation transformation based upon variations in the local terrain. The spectral and spatial modularity of the algorithm architecture allows the JPEG to be replaced by a totally different coder (e.g., DPCM). However. The significant practical advantage of this approach is that it is leveraged on the standard and highly developed JPEG compression technology. The algorithm is conveniently parameterized to accommodate reconstructed image fidelities ranging from near-lossless at about 5:1 compression ratio (CR) to visually lossy beginning at around 40:1 CR.< >

关键词： transform coding Karhunen-Loeve transforms Decorrelation Image coding Discrete cosine transforms Chromium Robustness Compression algorithms Multispectral imaging Standards development

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A new image coding technique unifying fractal and transform coding

A new image coding technique unifying fractal and transform ...

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IEEE International Conference on Image Processing

作者： K.U. Barthel J. Schuttemeyer T. Voye P. Noll Inst. fur Fernmeldetechnik Tech. Univ. Berlin Germany Institut Für Fernmeldetechnik Technische Universität Berlin Berlin Germany

We present a new image coding scheme based on an unification of fractal and transform coding. We introduce a generalization of the luminance transformation generally used by fractal coding schemes. By extending the luminance transformation to the frequency domain fractal and transform coding become subsets of the proposed transformation. Our new coding scheme FTC (fractal based transform coding) combines the advantages of both techniques. Compared to JPEG a coding gain of 1.5-2.5 dB (PSNR) is obtained. The encoding time is reduced compared to conventional fractal coding schemes and a better convergence at the decoder is attained. At equal error rates the subjective quality of images coded with the new scheme is superior compared to transform coded images.< >

关键词： Image coding Fractals transform coding Frequency domain analysis Gain PSNR Encoding Convergence Decoding Error analysis

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Modified ICA algorithms for finding optimal transforms in transform coding

Modified ICA algorithms for finding optimal transforms in tr...

引用

International Symposium on Image and Signal Processing and Analysis

作者： M. Narozny M. Barret D.-T. Pham I.P. Akam-Bita équipe Systèmes de Traitement du Signal France Laboratoire de Modélisation et Calcul IMAG France

In this paper we present two new algorithms that compute the linear optimal transform in high-rate transform coding, for non Gaussian data. One algorithm computes the optimal orthogonal transform, and the other the optimal linear transform. Comparison of the performances in high-rate transform coding between the classical Karhunen-Loeve transform (KLT) and the transforms returned by the new algorithms are given. On synthetic data, the transforms given by the new algorithms perform significantly better that the KLT, however on real data all the transforms, included KLT, give roughly the same coding gain.

关键词： Independent component analysis transform coding Karhunen-Loeve transforms Image coding Discrete wavelet transforms Vectors Quantization Discrete transforms Discrete cosine transforms Context modeling

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