Showing papers on "Data compression published in 1995"

Image quality measures and their performance

Abstract: A number of quality measures are evaluated for gray scale image compression. They are all bivariate, exploiting the differences between corresponding pixels in the original and degraded images. It is shown that although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques. A graphical measure called Hosaka plots, however, can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.

The context-tree weighting method: basic properties

Abstract: Describes a sequential universal data compression procedure for binary tree sources that performs the "double mixture." Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desirable coding distribution for tree sources with an unknown model and unknown parameters. Computational and storage complexity of the proposed procedure are both linear in the source sequence length. The authors derive a natural upper bound on the cumulative redundancy of the method for individual sequences. The three terms in this bound can be identified as coding, parameter, and model redundancy, The bound holds for all source sequence lengths, not only for asymptotically large lengths. The analysis that leads to this bound is based on standard techniques and turns out to be extremely simple. The upper bound on the redundancy shows that the proposed context-tree weighting procedure is optimal in the sense that it achieves the Rissanen (1984) lower bound. >

Rapid scene analysis on compressed video

Abstract: Several rapid scene analysis algorithms for detecting scene changes and flashlight scenes directly on compressed video are proposed. These algorithms operate on the DC sequence which can be readily extracted from video compressed using Motion JPEG or MPEG without full-frame decompression. The DC images occupy only a small fraction of the original data size while retaining most of the essential "global" information. Operating on these images offers a significant computation saving. Experimental results show that the proposed algorithms are fast and effective in detecting abrupt scene changes, gradual transitions including fade-ins and fade-outs, flashlight scenes and in deriving intrashot variations.

A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile

Abstract: To represent an image of high perceptual quality with the lowest possible bit rate, an effective image compression algorithm should not only remove the redundancy due to statistical correlation but also the perceptually insignificant components from image signals. In this paper, a perceptually tuned subband image coding scheme is presented, where a just-noticeable distortion (JND) or minimally noticeable distortion (MND) profile is employed to quantify the perceptual redundancy. The JND profile provides each signal being coded with a visibility threshold of distortion, below which reconstruction errors are rendered imperceptible. Based on a perceptual model that incorporates the threshold sensitivities due to background luminance and texture masking effect, the JND profile is estimated from analyzing local properties of image signals. According to the sensitivity of human visual perception to spatial frequencies, the full-band JND/MND profile is decomposed into component JND/MND profiles of different frequency subbands. With these component profiles, perceptually insignificant signals in each subband can be screened out, and significant signals can be properly encoded to meet the visibility threshold. A new quantitative fidelity measure, termed as peak signal-to-perceptible-noise ratio (PSPNR), is proposed to assess the quality of the compressed image by taking the perceptible part of the distortion into account. Simulation results show that near-transparent image coding can be achieved at less than 0.4 b/pixel. As compared to the ISO-JPEG standard, the proposed algorithm can remove more perceptual redundancy from the original image, and the visual quality of the reconstructed image is much more acceptable at low bit rates.

vic: a flexible framework for packet video

Abstract: The deployment of IP Multicast has fostered the development of a suite of applications, collectively known as the MBone tools, for real-time multimedia conferencing over the Internet. Two of these tools — nv from Xerox PARC and ivs from INRIA — provide video transmission using software-based codecs. We describe a new video tool, vic , that extends the groundbreaking work of nv and ivs with a more flexible system architecture. This flexibility is characterized by network layer independence, support for hardware-based codecs, a conference coordination model, an extensible user interface, and support for diverse compression algorithms. We also propose a novel compression scheme called “Intra-H.261”. Created as a hybrid of the nv and ivs codecs, Intra-H.261 provides a factor of 2–3 improvement in compression gain over the nv encoder (6 dB of PSNR) as well as a substantial improvement in run-time performance over the ivs H.261 coder.

Statistical properties of MPEG video traffic and their impact on traffic modeling in ATM systems

Abstract: MPEG video traffic is expected to cause several problems in ATM networks, both from performance and from architectural viewpoint. For the solution of these difficulties, appropriate video traffic models are needed. A detailed statistical analysis of newly generated long MPEG encoded video sequences is presented and the results are compared to those of existing data sets. Based on the results of the analysis, a layered modeling scheme for MPEG video traffic is suggested which will simplify the finding of appropriate models for a lot of performance analysis techniques.

Manipulation and compositing of MC-DCT compressed video

Abstract: Many advanced video applications require manipulations of compressed video signals. Popular video manipulation functions include overlap (opaque or semitransparent), translation, scaling, linear filtering, rotation, and pixel multiplication. We propose algorithms to manipulate compressed video in the compressed domain. Specifically, we focus on compression algorithms using the discrete cosine transform (DCT) with or without motion compensation (MC). Such compression systems include JPEG, motion JPEG, MPEG, and H.261. We derive a complete set of algorithms for all aforementioned manipulation functions in the transform domain, in which video signals are represented by quantized transform coefficients. Due to a much lower data rate and the elimination of decompression/compression conversion, the transform-domain approach has great potential in reducing the computational complexity. The actual computational speedup depends on the specific manipulation functions and the compression characteristics of the input video, such as the compression rate and the nonzero motion vector percentage. The proposed techniques can be applied to general orthogonal transforms, such as the discrete trigonometric transform. For compression systems incorporating MC (such as MPEG), we propose a new decoding algorithm to reconstruct the video in the transform domain and then perform the desired manipulations in the transform domain. The same technique can be applied to efficient video transcoding (e.g., from MPEG to JPEG) with minimal decoding. >

Projection-based spatially adaptive reconstruction of block-transform compressed images

Abstract: At the present time, block-transform coding is probably the most popular approach for image compression. For this approach, the compressed images are decoded using only the transmitted transform data. We formulate image decoding as an image recovery problem. According to this approach, the decoded image is reconstructed using not only the transmitted data but, in addition, the prior knowledge that images before compression do not display between-block discontinuities. A spatially adaptive image recovery algorithm is proposed based on the theory of projections onto convex sets. Apart from the data constraint set, this algorithm uses another new constraint set that enforces between-block smoothness. The novelty of this set is that it captures both the local statistical properties of the image and the human perceptual characteristics. A simplified spatially adaptive recovery algorithm is also proposed, and the analysis of its computational complexity is presented. Numerical experiments are shown that demonstrate that the proposed algorithms work better than both the JPEG deblocking recommendation and our previous projection-based image decoding approach. >

A tutorial on MPEG/audio compression

Abstract: This tutorial covers the theory behind MPEG/audio compression. While lossy, the algorithm can often provide "transparent", perceptually lossless compression, even with factors of 6-to-1 or more. It exploits the perceptual properties of the human auditory system. The article also covers the basics of psychoacoustic modeling and the methods the algorithm uses to compress audio data with the least perceptible degradation. >

Mosaic based representations of video sequences and their applications

Abstract: Recently, there has been a growing interest in the use of mosaic images to represent the information contained in video sequences. The paper systematically investigates how to go beyond thinking of the mosaic simply as a visualization device, but rather as a basis for efficient representation of video sequences. We describe two different types of mosaics called the static and the dynamic mosaic that are suitable for different needs and scenarios. We discuss a series of extensions to these basic mosaics to provide representations at multiple spatial and temporal resolutions and to handle 3D scene information. We describe techniques for the basic elements of the mosaic construction process, namely alignment, integration, and residual analysis. We describe several applications of mosaic representations including video compression, enhancement, enhanced visualization, and other applications in video indexing, search, and manipulation. >

Performance Study of a Selective Encryption Scheme for the Security of Networked, Real-Time Video

Abstract: Due to their large size, video images present a great challenge to currently available cryptographic algorithms; the computationally intensive processes of encryption and decryption of video images, introduce delays that are beyond acceptable realtime video application limits. In this paper, the Aegis mechanism is proposed. Aegis limits the amount of data to be encrypted or decrypted by using video compression to reduce the size of transmitted video images. The performance of Aegis (utilizing MPEG video compression across an ATM network) is explored through an extensive simulation study. Three types of video traffic: CATV, Stu&o TV, and video conference are considered. Our simulation results demonstrate the delay performance, as well as, the queue requirements for the Aegis encryption scheme versus the full encryption and no encryption schemes.

VLSI architectures for video compression-a survey

Abstract: The paper presents an overview on architectures for VLSI implementations of video compression schemes as specified by standardization committees of the ITU and ISO. VLSI implementation strategies are discussed and split into function specific and programmable architectures. As examples for the function oriented approach, alternative architectures for DCT and block matching will be evaluated. Also dedicated decoder chips are included Programmable video signal processors are classified and specified as homogeneous and heterogenous processor architectures. Architectures are presented for reported design examples from the literature. Heterogenous processors outperform homogeneous processors because of adaptation to the requirements of special, subtasks by dedicated modules. The majority of heterogenous processors incorporate dedicated modules for high performance subtasks of high regularity as DCT and block matching. By normalization to a fictive 1.0 /spl mu/m CMOS process typical linear relationships between silicon area and through-put rate have been determined for the different architectural styles. This relationship indicates a figure of merit for silicon efficiency. >

Scene change detection in an MPEG-compressed video sequence

Abstract: An algorithm is proposed for the detection of abrupt scene change and special editing effects such as dissolve in a compressed MPEG/MPEG-2 bitstream with minimal decoding of the bitstream. Scene changes are easily detected with DCT DC coefficients and motion vectors. By performing minimal decoding on the compressed bitstream, the processing speed for searching a video database of compressed image sequences can be dramatically improved. In addition, the algorithm may also be applied in video scene browsing and video indexing as well.

Image and video compression standards

Abstract: The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All prices exclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted. V. Bhaskaran, K. Konstantinides Image and Video Compression Standards

Video parsing and browsing using compressed data

Abstract: Parsing video content is an important first step in the video indexing process. This paper presents algorithms to automate the video parsing task, including partitioning a source video into clips and classifying those clips according to camera operations, using compressed video data. We have developed two algorithms and a hybrid approach to partitioning video data compressed according to the JPEG and MPEG standards. The algorithms utilize both the video content encoded in DCT (Discrete Cosine Transform) coefficients and the motion vectors between frames. The hybrid approach integrates the two algorithms and incorporates multi-pass strategies and motion analyses to improve both accuracy and processing speed. Also, we present content-based video browsing tools which utilize the information, particularly about the shot boundaries and key frames, obtained from parsing.

Radiologic image compression-a review

Abstract: The objective of radiologic image compression is to reduce the data volume of and to achieve a low bit rate in the digital representation of radiologic images without perceived loss of image quality. However, the demand for transmission bandwidth and storage space in the digital radiology environment, especially picture archiving and communication systems (PACS) and teleradiology, and the proliferating use of various imaging modalities, such as magnetic resonance imaging, computed tomography, ultrasonography, nuclear medicine, computed radiography, and digital subtraction angiography, continue to outstrip the capabilities of existing technologies. The availability of lossy coding techniques for clinical diagnoses further implicates many complex legal and regulatory issues. This paper reviews the recent progress of lossless and lossy radiologic image compression and presents the legal challenges of using lossy compression of medical records. To do so, we first describe the fundamental concepts of radiologic imaging and digitization. Then, we examine current compression technology in the field of medical imaging and discuss important regulatory policies and legal questions facing the use of compression in this field. We conclude with a summary of future challenges and research directions. >

Neural network approaches to image compression

Abstract: This paper presents a tutor a overview of neural networks as signal processing tools for image compression. They are well suited to the problem of image compression due to their massively parallel and distributed architecture. Their characteristics are analogous to some of the features of our own visual system, which allow us to process visual information with much ease. For example, multilayer perceptions can be used as nonlinear predictors in differential pulse-code modulation (DPCM). Such predictors have been shown to increase the predictive gain relative to a linear predictor. Another active area of research is in the application of Hebbian learning to the extraction of principal components, which are the basis vectors for the optimal linear Karhunen-Loeve transform (KLT). These learning algorithms are iterative, have some computational advantages over standard eigendecomposition techniques, and can be made to adapt to changes in the input signal. Yet another model, the self-organizing feature map (SOFM), has been used with a great deal of success in the design of codebooks for vector quantization (VQ). The resulting codebooks are less sensitive to initial conditions than the standard LBG algorithm, and the topological ordering of the entries can be exploited to further increasing the coding efficiency and reducing the computational complexity. >

CREW: Compression with Reversible Embedded Wavelets

Abstract: Compression with Reversible Embedded Wavelets (CREW) is a unified lossless and lossy continuous tone still image compression system. It is wavelet based using a "reversible" approximation of one of the best wavelet filters. Reversible wavelets are linear filters with non linear rounding which implement exact reconstruction systems with minimal precision integer arithmetic. Wavelet coefficients are encoded in a bit significance embedded order, allowing lossy compression by simply truncating the compressed data. For coding of coefficients, CREW uses a method similar to J. Shapiro's (1993) zero tree, and a completely novel method called Horizon. Horizon coding is a context based coding that takes advantage of the spatial and spectral information available in the wavelet domain. CREW provides state of the art lossless compression of medical images (greater than 8 bits deep), and lossy and lossless compression of 8 bit deep images with a single system. CREW has reasonable software and hardware implementations.

Model-based image coding advanced video coding techniques for very low bit-rate applications

Abstract: The paper gives an overview of model-based approaches applied to image coding, by looking at image source models. In these model-based schemes, which are different from the various conventional waveform coding methods, the 3-D properties of the scenes are taken into consideration. They can achieve very low bit rate image transmission. The 2-D model and 3-D model based approaches are explained. Among them, a 3-D model based method using a 3-D facial model and a 2-D model based method utilizing 2-D deformable triangular patches are described. Works related to 3-D model-based coding of facial images and some of the remaining problems are also described. >

Video and Image Processing in Multimedia Systems

Abstract: Part I: Introduction to Multimedia. 1. Basic Concepts. 2. Multimedia Networking and Synchronization. 3. Overview of Multimedia Applications. References. Part II: Multimedia Compression Techniques and Standards. 4. Introduction to Multimedia Compression. 5. JPEG Algorithm for Full-Color Still Image Compression. 6. PX64 Compression Algorithm for Video Telecommunications. 7. MPEG Compression for Motion-Intensive Applications. 8. Other Multimedia Compression Techniques. 9. Imlementations of Compression Algorithms. 10. Applications of Compression Systems. References. Part III: Image and Video Indexing and Retrieval Techniques. 11. Content-Based Image Retrieval. 12. Content-Based Video Indexing and Retrieval. 13. Video Processing Using Compressed Data. 14. A Case Study in Video Parsing: Television News. References. Index.

Unbounded length contexts for PPM

Abstract: The prediction by partial matching (PPM) data compression scheme has set the performance standard in lossless compression of text throughout the past decade. The original algorithm was first published in 1984 by Cleary and Witten, and a series of improvements was described by Moffat (1990), culminating in a careful implementation, called PPMC, which has become the benchmark version. This still achieves results superior to virtually all other compression methods, despite many attempts to better it. PPM, is a finite-context statistical modeling technique that can be viewed as blending together several fixed-order context models to predict the next character in the input sequence. Prediction probabilities for each context in the model are calculated from frequency counts which are updated adaptively; and the symbol that actually occurs is encoded relative to its predicted distribution using arithmetic coding. The paper describes a new algorithm, PPM*, which exploits contexts of unbounded length. It reliably achieves compression superior to PPMC, although our current implementation uses considerably greater computational resources (both time and space). The basic PPM compression scheme is described, showing the use of contexts of unbounded length, and how it can be implemented using a tree data structure. Some results are given that demonstrate an improvement of about 6% over the old method.

Video image compression using weighted wavelet hierarchical vector quantization

Abstract: A weighted wavelet hierarchical vector quantization (WWHVQ) procedure is initiated by obtaining an N×N pixel image where 8 bits per pixel (steps 10 and 12). A look-up operation is performed to obtain data representing a discrete wavelet transform (DWT) followed by a quantization of the data (step 14). Upon completion of the look-up, a data compression will have been performed. Further stages and look-up will result in further compression of the data, i.e., 4:1, 8:1, 16:1, 32:1, 64:1, . . . etc. Accordingly, a determination is made whether the compression is complete (step 16). If the compression is incomplete, further look-up is performed. If the compression is complete, however, the compressed data is transmitted (step 18). It is determined at a gateway whether further compression is required (step 19). If so, transcoding is performed (step 20). The receiver receives the compressed data (step 22). Subsequently, a second look-up operation is performed to obtain data representing an inverse discrete wavelet transform of the decompressed data (step 24). After one iteration, the data is decompressed by a factor of two. Further iterations allows for further decompression of the data. Accordingly, a determination is made whether decompression is complete (step 26). If the decompression is in incomplete, further look-ups are performed. If, however, the decompression is complete, the WWHVQ procedure is ended (step 28).

Byte-aligned bitmap compression

Abstract: Summary form only given. Bitmap compression reduces storage space and transmission time for unstructured bit sequences like in inverted files, spatial objects, etc. On the down side, the compressed bitmaps loose their functional properties. For example, checking a given bit position, set intersection, union, and difference can be performed only after full decoding, thus causing a many-folded operational speed degradation. The proposed byte-aligned bitmap compression method (BBC) aims to support fast set operations on the compressed bitmap formats and, at the same time, to retain a competitive compression rate. To achieve this objective, BBC abandons the traditional approach of encoding run-lengths (distances between two ones separated by zeros). Instead, BBC deals only with byte aligned byte-size bitmap portions that are easy to fetch, store, AND, OR, and convert. The bitmap bytes are classified as gaps containing only zeros or only ones and maps containing a mixture of both. We also introduced a simple extension mechanism for existing methods to accommodate a dual-gap (zeros and ones) run-length encoding. With this extension, encoding of long "one" sequences becomes as efficient and better than arithmetic encoding.

Statistical approach to scene change detection

Abstract: One of the challenging problems in video databases is the organization of video information. Segmenting a video into a number of clips and characterizing each clip has been suggested as one mechanism for organizing video information. This approach requires a suitable method to automatically locate cut points in a video. One way of finding such cut points is to determine the boundaries between consecutive camera shots. In this paper, we address this as a statistical hypothesis testing problem and present three tests to determine cut locations. All the three tests are such that they can be applied directly to the compressed video. This avoids an unnecessary decompression-compression cycle, since it is common to store and transmit digital video in compressed form. As our experimental results indicate, the statistical approach permits accurate detection of scene changes induced through straight as well as optical cuts.

On the modeling of DCT and subband image data for compression

Abstract: Image subband and discrete cosine transform coefficients are modeled for efficient quantization and noiseless coding. Quantizers and codes are selected based on Laplacian, fixed generalized Gaussian, and adaptive generalized Gaussian models. The quantizers and codes based on the adaptive generalized Gaussian models are always superior in mean-squared error distortion performance but, generally, by no more than 0.08 bit/pixel, compared with the much simpler Laplacian model-based quantizers and noiseless codes. This provides strong motivation for the selection of pyramid codes for transform and subband image coding. >

Digital compression of still images and video

Abstract: From the Publisher: Digital Compression of Still Images and Video is general in approach, and covers all the recognised coding algorithms, explaining their basic theory in enough detail to understand the principles involved, and discussing the results which have been achieved with them by research workers in all parts of the world. A brief historical review of the area is also included to orient those new to the field, and the work is supported by references spanning the period from the earliest work on time/frequency analysis, to the latest topic of research interest - image sequence transmission using asynchronous transfer mode (ATM) techniques.

A fast hierarchical motion vector estimation algorithm using mean pyramid

Abstract: In transmitting moving pictures, interframe coding is shown to be effective for compressing video data. A hierarchical motion vector estimation algorithm using mean pyramid is proposed. Using the same measurement window at each level of a pyramid, the proposed algorithm, based on the tree pruning, reduces the computational complexity greatly with its performance comparable to that of the full search (FS). By varying the number of candidate motion vectors which are to be used as the initial search points for motion vector estimation at the next level, the mean squared error of the proposed algorithm varies, ranging between those of the FS and three step search (TSS) methods. Also, depending on the number of candidate motion vectors, the computational complexity of the proposed hierarchical algorithm ranges from 1/8-1/2 of that of the FS. The computer simulation results of the proposed technique compared with the conventional methods are given for various test sequences. >

Database system with buffer manager providing per page native data compression and decompression

Abstract: A Client/Server Database System with improved methods for performing database queries, particularly DSS-type queries, is described. The system includes one or more Clients (e.g., Terminals or PCs) connected via a Network to a Server. In general operation, Clients store data in and retrieve data from one or more database tables resident on the Server by submitting SQL commands, some of which specify "queries"--criteria for selecting particular records of a table. The system implements methods for storing data vertically (i.e., by column), instead of horizontally (i.e., by row) as is traditionally done. Each column comprises a plurality of "cells" (i.e., column value for a record), which are arranged on a data page in a contiguous fashion. By storing data in a column-wise basis, the system can process a DSS query by bringing in only those columns of data which are of interest. Instead of retrieving row-based data pages consisting of information which is largely not of interest to a query, column-based pages can be retrieved consisting of information which is mostly, if not completely, of interest to the query. The retrieval itself can be done using more-efficient large block I/O transfers. The system includes data compression which is provided at the level of Cache or Buffer Managers, thus providing on-the-fly data compression in a manner which is transparent to each object. Since vertical storage of data leads to high repetition on a given data page, the system provides improved compression/decompression.

Vision based hand modeling and tracking for virtual teleconferencing and telecollaboration

Abstract: The authors present a hand model that simultaneously satisfies both the synthesis and analysis requirements of model based compression. The model can be fitted to any person's hand and can be done using a single camera. Once the model is fitted to a real human hand, it is then used in several tracking scenarios in order to verify its effectiveness. With successful tracking achieved, the model is ready to be incorporated into a virtual environment or model based compression scheme such as sign language communication over telephone lines or virtual teleconferences over computer networks at very low bit rates and at very high image quality. >

Compression of hyperspectral imagery using the 3-D DCT and hybrid DPCM/DCT

Abstract: Two systems are presented for compression of hyperspectral imagery which utilize trellis coded quantization (TCQ). Specifically, the first system uses TCQ to encode transform coefficients resulting from the application of an 8/spl times/8/spl times/8 discrete cosine transform (DCT). The second systems uses DPCM to spectrally decorrelate the data, while a 2D DCT coding scheme is used for spatial decorrelation. Side information and rate allocation strategies are discussed. Entropy-constrained code-books are designed using a modified version of the generalized Lloyd algorithm. These entropy constrained systems achieve compression ratios of greater than 70:1 with average PSNRs of the coded hyperspectral sequences exceeding 40.0 dB. >