Showing papers on "Data compression published in 1999"

High performance scalable image compression with EBCOT

Abstract: A new image compression algorithm is proposed, based on independent embedded block coding with optimized truncation of the embedded bit-streams (EBCOT). The algorithm exhibits state-of-the-art compression performance while producing a bit-stream with a rich feature set, including resolution and SNR scalability together with a random access property. The algorithm has modest complexity and is extremely well suited to applications involving remote browsing of large compressed images. The algorithm lends itself to explicit optimization with respect to MSE as well as more realistic psychovisual metrics, capable of modeling the spatially varying visual masking phenomenon.

Hidden digital watermarks in images

Abstract: An image authentication technique by embedding digital "watermarks" into images is proposed. Watermarking is a technique for labeling digital pictures by hiding secret information into the images. Sophisticated watermark embedding is a potential method to discourage unauthorized copying or attest the origin of the images. In our approach, we embed the watermarks with visually recognizable patterns into the images by selectively modifying the middle-frequency parts of the image. Several variations of the proposed method are addressed. The experimental results show that the proposed technique successfully survives image processing operations, image cropping, and the Joint Photographic Experts Group (JPEG) lossy compression.

Rate control in DCT video coding for low-delay communications

Abstract: An important motivation for the development of the emerging H.263+ and MPEG-4 coding standards is to enhance the quality of highly compressed video for two-way, real-time communications. In these applications, the delay produced by bits accumulated in the encoder buffer must be very small, typically below 100 ms, and the rate control strategy is responsible for encoding the video with high quality and maintaining a low buffer delay. In this work, we present a simple rate control technique that achieves these two objectives by smartly selecting the values of the quantization parameters in typical discrete cosine transform video coders. To do this, we derive models for bit rate and distortion in this type of coders, in terms of the quantization parameters. Using Lagrange optimization, we minimize distortion subject to the target bit constraint, and obtain formulas that indicate how to choose the quantization parameters. We implement our technique in H.263 and MPEG-4 coders, and compare its performance to TMN7 and VM7 rate control when the encoder buffer is small, for a variety of video sequences and bit rates. This new method has been adopted as a rate control tool in the test model TMN8 of H.263+ and (with some modifications) in the verification model VM8 of MPEG-4.

Edgebreaker: connectivity compression for triangle meshes

Abstract: Edgebreaker is a simple scheme for compressing the triangle/vertex incidence graphs (sometimes called connectivity or topology) of three-dimensional triangle meshes. Edgebreaker improves upon the storage required by previously reported schemes, most of which can guarantee only an O(t log(t)) storage cost for the incidence graph of a mesh of t triangles. Edgebreaker requires at most 2t bits for any mesh homeomorphic to a sphere and supports fully general meshes by using additional storage per handle and hole. For large meshes, entropy coding yields less than 1.5 bits per triangle. Edgebreaker's compression and decompression processes perform identical traversals of the mesh from one triangle to an adjacent one. At each stage, compression produces an op-code describing the topological relation between the current triangle and the boundary of the remaining part of the mesh. Decompression uses these op-codes to reconstruct the entire incidence graph. Because Edgebreaker's compression and decompression are independent of the vertex locations, they may be combined with a variety of vertex-compressing techniques that exploit topological information about the mesh to better estimate vertex locations. Edgebreaker may be used to compress the connectivity of an entire mesh bounding a 3D polyhedron or the connectivity of a triangulated surface patch whose boundary need not be encoded. The paper also offers a comparative survey of the rapidly growing field of geometric compression.

Image compression via joint statistical characterization in the wavelet domain

Abstract: We develop a probability model for natural images, based on empirical observation of their statistics in the wavelet transform domain. Pairs of wavelet coefficients, corresponding to basis functions at adjacent spatial locations, orientations, and scales, are found to be non-Gaussian in both their marginal and joint statistical properties. Specifically, their marginals are heavy-tailed, and although they are typically decorrelated, their magnitudes are highly correlated. We propose a Markov model that explains these dependencies using a linear predictor for magnitude coupled with both multiplicative and additive uncertainties, and show that it accounts for the statistics of a wide variety of images including photographic images, graphical images, and medical images. In order to directly demonstrate the power of the model, we construct an image coder called EPWIC (embedded predictive wavelet image coder), in which subband coefficients are encoded one bitplane at a time using a nonadaptive arithmetic encoder that utilizes conditional probabilities calculated from the model. Bitplanes are ordered using a greedy algorithm that considers the MSE reduction per encoded bit. The decoder uses the statistical model to predict coefficient values based on the bits it has received. Despite the simplicity of the model, the rate-distortion performance of the coder is roughly comparable to the best image coders in the literature.

The Art of Frame Theory

Abstract: Thye theory of frames for a Hilbert space plays a fundamental role in signal processing, image processing, data compression, sampling theory and much more, as well as being a fruitful area of research in abstract mathematics. In this ``tutorial'' on abstract frame theory, we will try to point out the major directions of research in abstract frame theory and give some sample techniques from each of the areas. We will also bring out some of the important open questions, discuss some of the limitations of the existing theory, and point to some new directions for research.

The application of multiwavelet filterbanks to image processing

Abstract: Multiwavelets are a new addition to the body of wavelet theory. Realizable as matrix-valued filterbanks leading to wavelet bases, multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible with scalar two-channel wavelet systems. After reviewing this theory, we examine the use of multiwavelets in a filterbank setting for discrete-time signal and image processing. Multiwavelets differ from scalar wavelet systems in requiring two or more input streams to the multiwavelet filterbank. We describe two methods (repeated row and approximation/deapproximation) for obtaining such a vector input stream from a one-dimensional (1-D) signal. Algorithms for symmetric extension of signals at boundaries are then developed, and naturally integrated with approximation-based preprocessing. We describe an additional algorithm for multiwavelet processing of two-dimensional (2-D) signals, two rows at a time, and develop a new family of multiwavelets (the constrained pairs) that is well-suited to this approach. This suite of novel techniques is then applied to two basic signal processing problems, denoising via wavelet-shrinkage, and data compression. After developing the approach via model problems in one dimension, we apply multiwavelet processing to images, frequently obtaining performance superior to the comparable scalar wavelet transform.

Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation

Abstract: Sparse coding is a method for finding a representation of data in which each of the components of the representation is only rarely significantly active. Such a representation is closely related to redundancy reduction and independent component analysis, and has some neurophysiological plausibility. In this article, we show how sparse coding can be used for denoising. Using maximum likelihood estimation of nongaussian variables corrupted by gaussian noise, we show how to apply a soft-thresholding (shrinkage) operator on the components of sparse coding so as to reduce noise. Our method is closely related to the method of wavelet shrinkage, but it has the important benefit over wavelet methods that the representation is determined solely by the statistical properties of the data. The wavelet representation, on the other hand, relies heavily on certain mathematical properties (like self-similarity) that may be only weakly related to the properties of natural data.

Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards

Abstract: Multimedia hardware still cannot accommodate the demand for large amounts of visual data Without the generation of high-quality video bitstreams, limited hardware capabilities will continue to stifle the advancement of multimedia technologies Thorough grounding in coding is needed so that applications such as MPEG-4 and JPEG 2000 may come to fruition Image and Video Compression for Multimedia Engineering provides a solid, comprehensive understanding of the fundamentals and algorithms that lead to the creation of new methods for generating high quality video bit streams The authors present a number of relevant advances along with international standards New to the Second Edition A chapter describing the recently developed video coding standard, MPEG-Part 10 Advances Video Coding also known as H264 Fundamental concepts and algorithms of JPEG2000 Color systems of digital video Up-to-date video coding standards and profiles Visual data, image, and video coding will continue to enable the creation of advanced hardware, suitable to the demands of new applications Covering both image and video compression, this book yields a unique, self-contained reference for practitioners tobuild a basis for future study, research, and development

A time-efficient and accurate strain estimation concept for ultrasonic elastography using iterative phase zero estimation

Abstract: In ultrasonic elastography, the exact estimation of temporal displacements between two signals is the key to estimating strain. An algorithm was previously proposed that estimates these displacements using phase differences of the corresponding base-band signals. A major advantage of these algorithms compared with correlation techniques is the computational efficiency. In this paper, an extension of the algorithm is presented that iteratively takes into account the time shifts of the signals to overcome the problems of aliasing and accuracy in the estimation of the phase shift. Thus, it can be proven that the algorithm is equivalent to the search of the maximum of the correlation function. Furthermore, a robust logarithmic compression is proposed that only compresses the envelope of the signal. This compression does not introduce systematic errors and significantly reduces decorrelation noise. The resulting algorithm is a computationally simple and very fast alternative to conventional correlation techniques, and the accuracy of strain images is improved.

Real-time Internet video using error resilient scalable compression and TCP-friendly transport protocol

Abstract: We introduce a point to point real-time video transmission scheme over the Internet combining a low-delay TCP-friendly transport protocol in conjunction with a novel compression method that is error resilient and bandwidth-scalable. Compressed video is packetized into individually decodable packets of equal expected visual importance. Consequently, relatively constant video quality can be achieved at the receiver under lossy conditions. Furthermore, the packets can be truncated to instantaneously meet the time varying bandwidth imposed by a TCP-friendly transport protocol. As a result, adaptive flows that are friendly to other Internet traffic are produced. Actual Internet experiments together with simulations are used to evaluate the performance of the compression, transport, and the combined schemes.

A review of the fractal image coding literature

Abstract: Fractal image compression is a technique based on the representation of an image by a contractive transform, on the space of images, for which the fixed point is close to the original image. This broad principle encompasses a very wide variety of coding schemes, many of which have been explored in the rapidly growing body of published research. While certain theoretical aspects of this representation are well established, relatively little attention has been given to the construction of a coherent underlying image model that would justify its use. Most purely fractal-based schemes are not competitive with the current state of the art, but hybrid schemes incorporating fractal compression and alternative techniques have achieved considerably greater success. This review represents a survey of the most significant advances, both practical and theoretical, since the publication of Jacquin's (1990) original fractal coding scheme.

Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising

Abstract: This paper deals with the application to denoising of a very simple but effective "local" spatially adaptive statistical model for the wavelet image representation that was previously introduced successfully in a compression context. Motivated by the intimate connection between compression and denoising, this paper explores the significant role of the underlying statistical wavelet image model. The model used here, a simplified version of the one proposed by LoPresto, Ramchandran and Orchard (see Proc. IEEE Data Compression Conf., 1997), is that of a mixture process of independent component fields having a zero-mean Gaussian distribution with unknown variances /spl sigma//sub s//sup 2/ that are slowly spatially-varying with the wavelet coefficient location s. We propose to use this model for image denoising by initially estimating the underlying variance field using a maximum likelihood (ML) rule and then applying the minimum mean squared error (MMSE) estimation procedure. In the process of variance estimation, we assume that the variance field is "locally" smooth to allow its reliable estimation, and use an adaptive window-based estimation procedure to capture the effect of edges. Despite the simplicity of our method, our denoising results compare favorably with the best reported results in the denoising literature.

Scan vector compression/decompression using statistical coding

Abstract: A compression/decompression scheme based on statistical coding is presented for reducing the amount of test data that must be stored on a tester and transferred to each core in a core-based design. The test vectors provided by the core vendor are stored in compressed form in the tester memory and transferred to the chip where they are decompressed and applied to the core. Given the set of test vectors for a core, a statistical code is carefully selected so that it satisfies certain properties. These properties guarantee that it can be decoded by a simple pipelined decoder (placed at the serial input of the core's scan chain) which requires very small area. Results indicate that the proposed scheme can use a simple decoder to provide test data compression near that of an optimal Huffman code. The compression results in a two-fold advantage since both test storage and test time are reduced.

Feedback-based error control for mobile video transmission

Abstract: We review feedback-based low bit-rate video coding techniques for robust transmission in mobile multimedia networks. For error control on the source coding level, each decoder has to make provisions for error detection, resynchronization, and error concealment, and we review techniques suitable for that purpose. Further, techniques are discussed for intelligent processing of acknowledgment information by the coding control to adapt the source coder to the channel. We review and compare error tracking, error confinement, and reference picture selection techniques for channel-adaptive source coding. For comparison of these techniques, a system for transmitting low bit-rate video over a wireless channel is presented and the performance is evaluated for a range of transmission conditions. We also show how feedback-based source coding can be employed in conjunction with precompressed video stored on a media server. The techniques discussed are applicable to a wide variety of interframe video schemes, including various video coding standards. Several of the techniques have been incorporated into the H.263 video compression standard, and this standard is used as an example throughout.

Fractal and Wavelet Image Compression Techniques

Abstract: Part 1 Fractal Image Compression: Iterated Function Systems Fractal Encoding of Grayscale Images Speeding Up Fractal Encoding. Part 2 Wavelet Image Compression: Simple Wavelets Daubechies Wavelets Wavelet Image Compression Techniques Comparison of Fractal and Wavelet Image Compression Appendix A - Using the Accompanying Software Appendix B - Utility Windows Library (UWL) Appendix C - Organization of the Accompanying Software Source Code.

Feedback-based error control for mobile video transmission : Video Transmission for Mobile Multimedia Applications

Abstract: We review feedback-based low bit-rate video coding techniques for robust transmission in mobile multimedia networks. For error control on the source coding level, each decoder has to make provisions for error detection, resynchronization, and error concealment, and we review techniques suitable for that purpose. Further, techniques are discussed for intelligent processing of acknowledgment information by the coding control to adapt the source coder to the channel. We review and compare error tracking, error confinement, and reference picture selection techniques for channel-adaptive source coding. For comparison of these techniques, a system for transmitting low bit-rate video over a wireless channel is presented and the performance is evaluated for a range of transmission conditions. We also show how feedback-based source coding can be employed in conjunction with precompressed video stored on a media server. The techniques discussed are applicable to a wide variety of interframe video schemes, including various video coding standards. Several of the techniques have been incorporated into the H.263 video compression standard recently, and this standard is used as an example throughout.

Compressing Integers for Fast File Access

Abstract: Fast access to files of integers is crucial for the efficient resolution of queries to databases. Integers are the basis of indexes used to resolve queries, for example, in large internet search systems, and numeric data forms a large part of most databases, Disk access costs can be reduced by compression, if the cost of retrieving a compressed representation from disk and the CPU cost of decoding such a representation is less than that of retrieving uncompressed data. In this paper we show experimentally that, for large or small collections, storing integers in a compressed format reduces the time required for either sequential stream access or random access. We compare different approaches to compressing integers, including the Elias gamma and delta codes, Golomb coding, and a variable-byte integer scheme. As a conclusion, we recommend that, for fast access to integers, files be stored compressed.

Offline dictionary-based compression

Abstract: Dictionary-based modelling is the mechanism used in many practical compression schemes. We use the full message (or a large block of it) to infer a complete dictionary in advance, and include an explicit representation of the dictionary as part of the compressed message. Intuitively, the advantage of this offline approach is that with the benefit of having access to all of the message, it should be possible to optimize the choice of phrases so as to maximize compression performance. Indeed, we demonstrate that very good compression can be attained by an offline method without compromising the fast decoding that is a distinguishing characteristic of dictionary-based techniques. Several nontrivial sources of overhead, in terms of both computation resources required to perform the compression, and bits generated into the compressed message, have to be carefully managed as part of the offline process. To meet this challenge, we have developed a novel phrase derivation method and a compact dictionary encoding. In combination these two techniques produce the compression scheme RE-PAIR, which is highly efficient, particularly in decompression.

Feature-preserving data compression of stamping tonnage information using wavelets

Abstract: Tonnage information is referred to as stamping force measurement in a complete forming cycle. Tonnage data contains rich information and features of stamping process failures. Due to its nonstationary nature and lack of physical engineering models, tonnage information cannot be effectively compressed using conventional data-compression techniques. This article presents a statistical method for “feature-preserving” data compression of tonnage information using wavelets. The technique provides more effcient data-compression results while maintaining key information and features for process monitoring and diagnosis. Detailed criteria, algorithms, and procedures are presented. A real case study is provided to illustrate the developed concepts and algorithms.

Blur determination in the compressed domain using DCT information

Abstract: The paper presents a simple yet robust measure of image quality in terms of global (camera) blur. It is based on histogram computation of non-zero DCT coefficients. The technique is directly applicable to images and video frames in compressed (MPEG or JPEG) domain and to all types of MPEG frames (I-, P- or B-frames). The resulting quality measure is proved to be in concordance with subjective testing and is therefore suitable for quick qualitative characterization of images and video frames.

Image and Video Compression for Multimedia Engineering

Abstract: From the Publisher: Image and Video Compression for Multimedia Engineering provides a solid, comprehensive understanding of the fundamentals and algorithms of coding and details all of the relevant international coding standards "With the growing popularity of applications that use large amounts of visual data, image and video coding is an active and dynamic field Image and Video Compression for Multimedia Engineering is a first, comprehensive graduate/senior level text and a self-contained reference for researchers and engineers that builds a basis for future study, research, and development

System and method for performing scalable embedded parallel data compression

Abstract: A system and method for performing parallel data compression which processes stream data at more than a single byte or symbol (character) at one time. The parallel compression engine modifies a single stream dictionary based (or history table based) data compression method, such as that described by Lempel and Ziv, to provide a scalable, high bandwidth compression. The parallel compression method examines a plurality of symbols in parallel, thus providing greatly increased compression performance. The method first involves receiving uncompressed data, wherein the uncompressed data comprises a plurality of symbols. The method maintains a history table comprising entries, wherein each entry comprises at least one symbol. The method operates to compare a plurality of symbols with entries in the history table in a parallel fashion, wherein this comparison produces compare results. The method then determines match information for each of the plurality of symbols based on the compare results. The step of determining match information involves determining zero or more matches of the plurality of symbols with each entry in the history table. The method then outputs compressed data in response to the match information.

Video Coding: An Introduction to Standard Codecs

Abstract: From the Publisher: This book gives an introduction to video coding algorithms, working up from basic principles through to the advanced video compression systems now being developed. The main objective is to describe the reasons behind the introduction of a standard codec for a specific application and its chosen parameters. The book should enable readers to appreciate the fundamental elements needed to design a video codec for a given application.

Principles and applications of BPCS steganography

Abstract: Steganography is a technique to hide secret information in some other data (we call it a vessel) without leaving any apparent evidence of data alteration. All of the traditional steganographic techniques have limited information-hiding capacity. They can hide only 10% (or less) of the data amounts of the vessel. This is because the principle of those techniques was either to replace a special part of the frequency components of the vessel image, or to replace all the least significant bits of a multivalued image with the secret information. Our new steganography uses an image as the vessel data, and we embed secret information in the bit-planes of the vessel. This technique makes use of the characteristics of the human vision system whereby a human cannot perceive any shape information in a very complicated binary pattern. We can replace all of the noise-like regions in the bit-planes of the vessel image with secret data without deteriorating the image quality. We termed our steganography BPCS-Steganography, which stands for Bit-Plane Complexity Segmentation Steganography. We made an experimental system to investigate this technique in depth. The merits of BPCS-Steganography found by the experiments are as follows. 1. The information hiding capacity of a true color image is around 50%. 2. A sharpening operation on the dummy image increases the embedding capacity quite a bit. 3. Canonical Gray coded bit planes are more suitable for BPCS-Steganography than the standard binary bit planes. 4. Randomization of the secret data by a compression operation makes the embedded data more intangible. 5. Customization of a BPCS-Steganography program for each user is easy. It further protects against eavesdropping on the embedded information.

Adaptive motion-vector resampling for compressed video downscaling

Abstract: Digital video is becoming widely available in compressed form, such as a motion JPEG or MPEG coded bitstream. In applications such as video browsing or picture-in-picture, or in transcoding for a lower bit rate, there is a need to downscale the video prior to its transmission. In such instances, the conventional approach to generating a downscaled video bitstream at the video server would be to first decompress the video, perform the downscaling operation in the pixel domain, and then recompress it as, say, an MPEG, bitstream for efficient delivery. This process is computationally expensive due to the motion-estimation process needed during the recompression phase. We propose an alternative compressed domain-based approach that computes motion vectors for the downscaled (N/2xN/2) video sequence directly from the original motion vectors for the N/spl times/N video sequence. We further discover that the scheme produces better results by weighting the original motion vectors adaptively. The proposed approach can lead to significant computational savings compared to the conventional spatial (pixel) domain approach. The proposed approach is useful for video severs that provide quality of service in real time for heterogeneous clients.

Image coding based on a morphological representation of wavelet data

Abstract: An experimental study of the statistical properties of wavelet coefficients of image data is presented, as well as the design of two different morphology-based image coding algorithms that make use of these statistics. A salient feature of the proposed methods is that, by a simple change of quantizers, the same basic algorithm yields high performance embedded or fixed rate coders. Another important feature is that the shape information of morphological sets used in this coder is encoded implicitly by the values of wavelet coefficients, thus avoiding the use of explicit and rate expensive shape descriptors, these proposed algorithms, while achieving nearly the same objective performance of state-of-the-art zerotree based methods, are able to produce reconstructions of a somewhat superior perceptual quality, due to a property of joint compression and noise reduction they exhibit.

Image compression with neural networks } A survey

Abstract: Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to vector quantization have now become well established, and other aspects of neural network involvement in this area are stepping up to play significant roles in assisting with those traditional technologies. This paper presents an extensive survey on the development of neural networks for image compression which covers three categories: direct image compression by neural networks; neural network implementation of existing techniques, and neural network based technology which provide improvement over traditional algorithms.

Spatial-temporal distortion metric for in-service quality monitoring of any digital video system

Abstract: Many organizations have focused on developing digital video quality metrics which produce results that accurately emulate subjective responses. However, to be widely applicable a metric must also work over a wide range of quality, and be useful for in-service quality monitoring. The Institute for Telecommunication Sciences (ITS) has developed spatial-temporal distortion metrics that meet all of these requirements. These objective metrics are described in detail and have a number of interesting properties, including utilization of 1) spatial activity filters which emphasize long edges on the order of 1/5 degree while simultaneously performing large amounts of noise suppression, 2) the angular direction of the spatial gradient, 3) spatial-temporal compression factors of at least 384:1 (spatial compression of at least 64:1 and temporal compression of at least 6:1, and 4) simple perceptibility thresholds and spatial-temporal masking functions. Results are presented that compare the objective metric values with mean opinion scores from a wide range of subjective data bases spanning many different scenes, systems, bit-rates, and applications.

Multiresolution watermarking for images and video

Abstract: This paper proposes a unified approach to digital watermarking of images and video based on the two- and three-dimensional discrete wavelet transforms. The hierarchical nature of the wavelet representation allows multiresolutional detection of the digital watermark, which is a Gaussian distributed random vector added to all the high-pass bands in the wavelet domain. We show that when subjected to distortion from compression or image halftoning, the corresponding watermark can still be correctly identified at each resolution (excluding the lowest one) in the wavelet domain. Computational savings from such a multiresolution watermarking framework is obvious, especially for the video case.