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检索条件"主题词=predictive coding"

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New statistical models of the JPEG lossless mode subject to the super high definition images

New statistical models of the JPEG lossless mode subject to ...

引用

IEEE International Conference on Image Processing

作者： Y. Kuroki Y. Ueshige T. Ohta Department of Electrical Engineering Kagoshima National College of Technology Kagoshima Japan Department of Electrical Engineering Kyushu Institute of Technology Fukuoka Japan

This paper describes new statistical models of the JPEG lossless mode subject to the super high definition images (SHDI). Seven predictors prepared in the JPEG are very simple to alleviate the complexity of the prediction process, which indicates that prediction residuals correlate. The actual correlation of the residuals exhibits a tendency to be more significant as the number of picture elements increases. Consequently, the conditional probability densities of the residual signals for SHDI differ from the Laplacian distribution commonly assumed in predictive coding. We propose two statistical models considering the peculiar probability densities and investigate the validity of the models by coding simulations.

关键词： Decision trees Probability predictive coding Image coding predictive models Encoding Pixel Educational institutions Laplace equations Redundancy

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Polynomial Weighted Median Predictors for Image Sequences

Polynomial Weighted Median Predictors for Image Sequences

引用

IEEE International Conference on Image Processing

作者： Binwei Weng Tuncer C. Aysal Kenneth E. Barner Department of Electrical and Computer Engineering University of Delaware Newark DE USA

Image sequence prediction is widely used in image compression and transmission schemes such as differential pulse code modulation (DPCM). In traditional predictive coding, linear predictors are usually adopted to exploit the inherent redundancy and correlation between neighboring pixels. However, due to the nonstationary and non-Gaussian nature of image sequences, linear predictors are not often very effective. As an alternative, Volterra predictor is able to compensate for the smoothing effects introduced by linear predictor. However, it suffers from noise that may be attributed to quantization errors or image acquisition devices. In this paper, we propose a novel nonlinear polynomial weighted median (PWM) predictor for image sequence prediction. The proposed PWM predictor is more robust to noise, while still retaining the information of higher-order statistics of pixel values. Experimental results illustrate that the PWM predictor yields better results than other predictors especially in noisy case. The proposed scheme can be incorporated in new predictive coding systems.

关键词： Polynomials Image sequences Pulse width modulation Pulse modulation predictive coding Image coding Pulse compression methods Modulation coding Redundancy Smoothing methods

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Lossy compression of clustered-dot halftones using sub-cell prediction

Lossy compression of clustered-dot halftones using sub-cell ...

引用

Data Compression Conference (DCC)

作者： R.A. Vander Kam R.M. Gray Information Systems Laboratory University of Stanford Stanford CA USA

We propose a predictive coding algorithm for lossy compression of digital halftones produced by clustered-dot dithering. In our scheme, the predictor estimates the size and shape of each halftone dot (cluster) based on the characteristics of neighboring clusters. The prediction template depends on which portion, or sub-cell, of the dithering matrix produced the dot. Information loss is permitted through imperfect representation of the prediction residuals. For some clusters, no residual is transmitted at all, and for others, information about the spatial locations of bit errors is omitted. Specifying only the number of bit errors in the residual is enough to allow the decoder to form an excellent approximation to the original dot structure. We also propose a simple alternative to the ordinary Hamming distance for computing distortion in bi-level images. Experiments with 1024/spl times/1024 images, 8/spl times/8 dithering cells, and 600 dpi printing have shown that the coding algorithm maintains good image quality while achieving rates below 0.1 bits per pixel.

关键词： predictive coding Clustering algorithms Prediction algorithms Shape Decoding Hamming distance Printing Image coding Image quality Pixel

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Unconstrained motion compensated temporal filtering (UMCTF) framework for wavelet video coding

Unconstrained motion compensated temporal filtering (UMCTF) ...

引用

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

作者： M. van der Schaar D.S. Turaga Philips Research USA

The paper presents a new framework for adaptive temporal filtering in wavelet interframe codecs, called unconstrained motion compensated temporal filtering (UMCTF). This framework allows flexible and efficient temporal filtering by combining the best features of motion compensation, used in predictive coding, with the advantages of interframe scalable wavelet video coding schemes. UMCTF provides higher coding efficiency, improved visual quality and flexibility of temporal and spatial scalability, higher coding efficiency and lower decoding delay than conventional MCTF schemes. Furthermore, UMCTF can also be employed in alternative open-loop scalable coding frameworks using DCT for the texture coding.

关键词： Filtering Video coding Adaptive filters Codecs Motion compensation predictive coding Scalability Decoding Delay Discrete cosine transforms

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Sprite-based video coding using on-line segmentation

Sprite-based video coding using on-line segmentation

引用

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

作者： R. Crinon I. Sezan Sharp Laboratories of America Inc.orporated Camas WA USA

We address the problem of on-line sprite-based video coding in cases where scene segmentation is not available a priori or transmission of such segmentation information cannot be afforded due to low bit rate requirements. We propose an on-line segmentation method that can be integrated into an MPEG4 on-line sprite based video codec. The proposed method uses macroblock types as well as motion compensated residuals to perform the on-line segmentation. It produces a background mosaic without requiring a priori foreground-background segmentation information. Our results demonstrate the coding efficiency and functionality benefits of the proposed approach.

关键词： Video coding Image segmentation MPEG 4 Standard Video compression Image coding Layout Bit rate Video codecs predictive coding Decoding

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Some experimental results in adaptive prediction DPCM coding of images

Some experimental results in adaptive prediction DPCM coding...

引用

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

作者： I. Paul J. Woods Bell Laboratories Holmdel NJ USA Rensselaer Polytechnic Institute Troy NY USA

In this paper we present results from our work on adaptive prediction dpcm for grey level images using the doubly stochastic Gaussian image model. This model consists of a lower level level 2-D Markov chain which takes on L different values and correspondingly L different sets of predictor parameters for an upper level conditionally Gaussian field. A simple gradient based algorithm which uses fuzzy decision theory is used to identify the lower level chain from observations on the upper level field, i.e. the actual image. The upper level field is encoded by 2-D DPCM using spatially varying predictors as determined by the lower level chain. For our simulations L was chosen to be 5, with 4 models representing edges at 0, 45, 90, and 135 degrees and the fifth model representing the non-edge regions. Both fixed and adaptive (Jayant type) quantizers were used. Greater compression is achieved by subsampling in the non-edge regions of the image and then interpolating at the decoder.

关键词： Image coding Stochastic processes predictive models Transform coding Statistics Sociotechnical systems Decision theory Decoding Standards development predictive coding

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Improved pel-recursive motion estimation algorithms

Improved pel-recursive motion estimation algorithms

引用

IEEE Southeastcon

作者： S. Liu M. Hayes N. Faust School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA EOD-EML Branch 0800-Baker Georgia Tech Research Institute Georgia Institute of Technology Atlanta GA USA

The pel-recursive approach to motion estimation is studied. Two algorithms that model the spatial gradient as an estimate plus noise are derived. The first algorithm deals with the usual two-frame case, except that damping terms are introduced in the gradient covariance matrix. Simulations show that this algorithm is stable enough that no restriction on the maximum allowable updating step size is required. The second algorithm is an extension of the first algorithm to the general multiframe case. The algorithms are tested and compared using synthetic and real video sequences, and it is shown that using more than two frames simultaneously can track motion more accurately in noisy environments.< >

关键词： Motion estimation Motion compensation Video coding predictive coding Linear predictive coding Video sequences Recursive estimation Approximation algorithms Damping Covariance matrix

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A Framework for Explainable Text Classification in Legal Document Review

A Framework for Explainable Text Classification in Legal Doc...

引用

IEEE International Conference on Big Data

作者： Christian J. Mahoney Jianping Zhang Nathaniel Huber-Fliflet Peter Gronvall Haozhen Zhao e-Discovery Cleary Gottlieb Steen & Hamilton LLP Washington DC USA Data & Technology Ankura Consulting Group LLC DC Washington

ISBN: (数字)9781728108582

ISBN: (纸本)9781728108599

Companies regularly spend millions of dollars producing electronically-stored documents in legal matters. Over the past two decades, attorneys have been using a variety of technologies to conduct this exercise, and most recently, parties on both sides of the `legal aisle' are accepting the use of machine learning techniques like text classification to cull massive volumes of data and to identify responsive documents for use in these matters. While text classification is regularly used to reduce the discovery costs in legal matters, text classification also faces a peculiar perception challenge: amongst lawyers, this technology is sometimes looked upon as a black box Put simply, very little information is provided for attorneys to understand why documents are classified as responsive. In recent years, a group of AI and Machine Learning researchers have been actively researching Explainable AI. In an explainable AI system, actions or decisions are human understandable. In legal `document review' scenarios, a document can be identified as responsive, as long as one or more of the text snippets (small passages of text) in a document are deemed responsive. In these scenarios, if text classification can be used to locate these responsive snippets, then attorneys could easily evaluate the model's document classification decision. When deployed with defined and explainable results, text classification can drastically enhance the overall quality and speed of the document review process by reducing the time it takes to review documents. Moreover, explainable predictive coding provides lawyers with greater confidence in the results of that supervised learning task. This paper describes a framework for explainable text classification as a valuable tool in legal services: for enhancing the quality and efficiency of legal document review and for assisting in locating responsive snippets within responsive documents. This framework has been implemented in our legal analytics produc

关键词： Text categorization Law Machine learning predictive coding predictive models

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A New Adaptive Blending Predictor for Lossless Image Compression

A New Adaptive Blending Predictor for Lossless Image Compres...

引用

ITI International Conference on Information and Communications Technology (ICICT)

作者： J. Knezovic M. Kovac H. Mlinaric Faculty ofElectrical Engineering and Computing University of Zagreb Croatia

Summary form only given. In the paper we propose a new adaptive predictor which is based on the blending of multiple static predictors on the dynamically classified causal set of neighboring pixels. The predictor models the image properties around the current, unknown pixel and adjusts itself to the local image region. The main contribution of this work is the enhancement of the well known approach of predictor blends through highly adaptive determination of blending context on a pixel-by-pixel basis using classification technique. This allows modeling of more complex image structures such as nontrivially oriented edges and the periodicity and coarseness of textures.

关键词： Image coding Pixel predictive models predictive coding Biomedical imaging

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Capturing Temporal Dependencies Through Future Prediction for CNN-Based Audio Classifiers

Capturing Temporal Dependencies Through Future Prediction fo...

引用

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

作者： Hongwei Song Jiqing Han Shiwen Deng Zhihao Du School of Computer Science and Technology Harbin Institute of Technology China School of Mathematical Science Harbin Normal University China

This paper focuses on the problem of temporal dependency modeling in the CNN-based models for audio classification tasks. To capture audio temporal dependencies using CNNs, we take a different approach from the purely architecture-induced method and explicitly encode temporal dependencies into the CNN-based audio classifiers. More specifically, in addition to the classification objective, we require the CNN model to solve an auxiliary task of predicting the future features, which is formulated by leveraging the Contrastive predictive coding (CPC) loss. Furthermore, a novel hierarchical CPC (HCPC) model is proposed for capturing multi-level temporal dependencies at the same time. The proposed model is evaluated on a wide range of non-speech audio signals, including musical and in-the-wild environmental audio signals. We show that the proposed approach improves the backbone CNNs consistently on all tested benchmark datasets and outperforms a DenseNet model trained from scratch.

关键词： Speech coding Conferences Music predictive models predictive coding Signal processing Benchmark testing

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