Showing papers on "Data compression published in 2001"

The JPEG 2000 still image compression standard

Abstract: One of the aims of the standardization committee has been the development of Part I, which could be used on a royalty- and fee-free basis. This is important for the standard to become widely accepted. The standardization process, which is coordinated by the JTCI/SC29/WG1 of the ISO/IEC has already produced the international standard (IS) for Part I. In this article the structure of Part I of the JPFG 2000 standard is presented and performance comparisons with established standards are reported. This article is intended to serve as a tutorial for the JPEG 2000 standard. The main application areas and their requirements are given. The architecture of the standard follows with the description of the tiling, multicomponent transformations, wavelet transforms, quantization and entropy coding. Some of the most significant features of the standard are presented, such as region-of-interest coding, scalability, visual weighting, error resilience and file format aspects. Finally, some comparative results are reported and the future parts of the standard are discussed.

Color and texture descriptors

Abstract: This paper presents an overview of color and texture descriptors that have been approved for the Final Committee Draft of the MPEG-7 standard. The color and texture descriptors that are described in this paper have undergone extensive evaluation and development during the past two years. Evaluation criteria include effectiveness of the descriptors in similarity retrieval, as well as extraction, storage, and representation complexities. The color descriptors in the standard include a histogram descriptor that is coded using the Haar transform, a color structure histogram, a dominant color descriptor, and a color layout descriptor. The three texture descriptors include one that characterizes homogeneous texture regions and another that represents the local edge distribution. A compact descriptor that facilitates texture browsing is also defined. Each of the descriptors is explained in detail by their semantics, extraction and usage. The effectiveness is documented by experimental results.

Multiple description coding: compression meets the network

Abstract: This article focuses on the compressed representations of pictures. The representation does not affect how many bits get from the Web server to the laptop, but it determines the usefulness of the bits that arrive. Many different representations are possible, and there is more involved in their choice than merely selecting a compression ratio. The techniques presented represent a single information source with several chunks of data ("descriptions") so that the source can be approximated from any subset of the chunks. By allowing image reconstruction to continue even after a packet is lost, this type of representation can prevent a Web browser from becoming dormant.

Overview of fine granularity scalability in MPEG-4 video standard

Abstract: Streaming video profile is the subject of an Amendment of MPEG-4, and is developed in response to the growing need on a video coding standard for streaming video over the Internet. It provides the capability to distribute single-layered frame-based video over a wide range of bit rates with high coding efficiency. It also provides fine granularity scalability (FGS), and its combination with temporal scalability, to address a variety of challenging problems in delivering video over the Internet. This paper provides an overview of the FGS video coding technique in this Amendment of the MPEG-4.

A robust image authentication method distinguishing JPEG compression from malicious manipulation

Abstract: Image authentication verifies the originality of an image by detecting malicious manipulations. Its goal is different from that of image watermarking, which embeds into the image a signature surviving most manipulations. Most existing methods for image authentication treat all types of manipulation equally (i.e., as unacceptable). However, some practical applications demand techniques that can distinguish acceptable manipulations (e.g., compression) from malicious ones. In this paper, we present an effective technique for image authentication which can prevent malicious manipulations but allow JPEG lossy compression. The authentication signature is based on the invariance of the relationships between discrete cosine transform (DCT) coefficients at the same position in separate blocks of an image. These relationships are preserved when DCT coefficients are quantized in JPEG compression. Our proposed method can distinguish malicious manipulations from JPEG lossy compression regardless of the compression ratio or the number of compression iterations. We describe adaptive methods with probabilistic guarantee to handle distortions introduced by various acceptable manipulations such as integer rounding, image filtering, image enhancement, or scaling-recaling. We also present theoretical and experimental results to demonstrate the effectiveness of the technique.

An analysis of the Burrows—Wheeler transform

Abstract: The Burrows—Wheeler Transform (also known as Block-Sorting) is at the base of compression algorithms that are the state of the art in lossless data compression In this paper, we analyze two algorithms that use this technique The first one is the original algorithm described by Burrows and Wheeler, which, despite its simplicity outperforms the Gzip compressor The second one uses an additional run-length encoding step to improve compression We prove that the compression ratio of both algorithms can be bounded in terms of the kth order empirical entropy of the input string for any k ≥ 0 We make no assumptions on the input and we obtain bounds which hold in the worst case that is for every possible input string All previous results for Block-Sorting algorithms were concerned with the average compression ratio and have been established assuming that the input comes from a finite-order Markov source

System-on-a-chip test-data compression and decompression architectures based on Golomb codes

Abstract: We present a new test-data compression method and decompression architecture based on variable-to-variable-length Golomb codes. The proposed method is especially suitable for encoding precomputed test sets for embedded cores in a system-on-a-chip (SoC). The major advantages of Golomb coding of test data include very high compression, analytically predictable compression results, and a low-cost and scalable on-chip decoder. In addition, the novel interleaving decompression architecture allows multiple cores in an SoC to be tested concurrently using a single automatic test equipment input-output channel. We demonstrate the effectiveness of the proposed approach by applying it to the International Symposium on Circuits and Systems' benchmark circuits and to two industrial production circuits. We also use analytical and experimental means to highlight the superiority of Golomb codes over run-length codes.

A framework for efficient progressive fine granularity scalable video coding

Abstract: A basic framework for efficient scalable video coding, namely progressive fine granularity scalable (PFGS) video coding is proposed. Similar to the fine granularity scalable (PGS) video coding in MPEG-4, the PFGS framework has all the features of FGS, such as fine granularity bit-rate scalability, channel adaptation, and error recovery. On the other hand, different from the PGS coding, the PFGS framework uses multiple layers of references with increasing quality to make motion prediction more accurate for improved video-coding efficiency. However, using multiple layers of references with different quality also introduces several issues. First, extra frame buffers are needed for storing the multiple reconstructed reference layers. This would increase the memory cost and computational complexity of the PFGS scheme. Based on the basic framework, a simplified and efficient PFGS framework is further proposed. The simplified PPGS framework needs only one extra frame buffer with almost the same coding efficiency as in the original framework. Second, there might be undesirable increase and fluctuation of the coefficients to be coded when switching from a low-quality reference to a high-quality one, which could partially offset the advantage of using a high-quality reference. A further improved PFGS scheme can eliminate the fluctuation of enhancement-layer coefficients when switching references by always using only one high-quality prediction reference for all enhancement layers. Experimental results show that the PFGS framework can improve the coding efficiency up to more than 1 dB over the FGS scheme in terms of average PSNR, yet still keeps all the original properties, such as fine granularity, bandwidth adaptation, and error recovery. A simple simulation of transmitting the PFGS video over a wireless channel further confirms the error robustness of the PFGS scheme, although the advantages of PFGS have not been fully exploited.

Fast multiplierless approximations of the DCT with the lifting scheme

Abstract: We present the design, implementation, and application of several families of fast multiplierless approximations of the discrete cosine transform (DCT) with the lifting scheme called the binDCT. These binDCT families are derived from Chen's (1977) and Loeffler's (1989) plane rotation-based factorizations of the DCT matrix, respectively, and the design approach can also be applied to a DCT of arbitrary size. Two design approaches are presented. In the first method, an optimization program is defined, and the multiplierless transform is obtained by approximating its solution with dyadic values. In the second method, a general lifting-based scaled DCT structure is obtained, and the analytical values of all lifting parameters are derived, enabling dyadic approximations with different accuracies. Therefore, the binDCT can be tuned to cover the gap between the Walsh-Hadamard transform and the DCT. The corresponding two-dimensional (2-D) binDCT allows a 16-bit implementation, enables lossless compression, and maintains satisfactory compatibility with the floating-point DCT. The performance of the binDCT in JPEG, H.263+, and lossless compression is also demonstrated.

Digital video quality metric based on human vision

Abstract: The growth of digital video has given rise to a need for computational methods for evaluating the visual quality of digital video. We have developed a new digital video quality metric, which we call DVQ (digital video quality) (A. B. Watson, in Human Vision, Visual Processing, and Digital Display VIII, Proc. SPIE 3299, 139- 147 (1998)). Here, we provide a brief description of the metric, and give a preliminary report on its performance. DVQ accepts a pair of digital video sequences, and computes a measure of the magnitude of the visible difference between them. The metric is based on the discrete cosine transform. It incorporates aspects of early visual pro- cessing, including light adaptation, luminance, and chromatic chan- nels; spatial and temporal filtering; spatial frequency channels; con- trast masking; and probability summation. It also includes primitive dynamics of light adaptation and contrast masking. We have applied the metric to digital video sequences corrupted by various typical compression artifacts, and compared the results to quality ratings made by human observers. © 2001 SPIE and IS&T. (DOI: 10.1117/1.1329896)

Performance analysis of image compression using wavelets

Abstract: The aim of this paper is to examine a set of wavelet functions (wavelets) for implementation in a still image compression system and to highlight the benefit of this transform relating to today's methods. The paper discusses important features of wavelet transform in compression of still images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression. Image quality is measured objectively, using peak signal-to-noise ratio or picture quality scale, and subjectively, using perceived image quality. The effects of different wavelet functions, image contents and compression ratios are assessed. A comparison with a discrete-cosine-transform-based compression system is given. Our results provide a good reference for application developers to choose a good wavelet compression system for their application.

A fast scheme for image size change in the compressed domain

Abstract: Given a video frame in terms of its 8/spl times/8 block-DCT coefficients, we wish to obtain a downsized or upsized version of this frame also in terms of 8/spl times/8 block-DCT coefficients. The DCT being a linear unitary transform is distributive over matrix multiplication. This fact has been used for downsampling video frames in the DCT domain. However, this involves matrix multiplication with the DCT of the downsampling matrix. This multiplication can be costly enough to trade off any gains obtained by operating directly in the compressed domain. We propose an algorithm for downsampling and also upsampling in the compressed domain which is computationally much faster, produces visually sharper images, and gives significant improvements in PSNR (typically 4-dB better compared to bilinear interpolation). Specifically the downsampling method requires 1.25 multiplications and 1.25 additions per pixel of original image compared to 4.00 multiplications and 4.75 additions required by the method of Chang et al. (1995). Moreover, the downsampling and upsampling schemes combined together preserve all the low-frequency DCT coefficients of the original image. This implies tremendous savings for coding the difference between the original frame (unsampled image) and its prediction (the upsampled image). This is desirable for many applications based on scalable encoding of video. The method presented can also be used with transforms other than DCT, such as Hadamard or Fourier.

Low-delay rate control for DCT video coding via /spl rho/-domain source modeling

Abstract: By introducing the new concepts of characteristic rate curves and rate curve decomposition, a generic source-modeling framework is developed for transform coding of videos. Based on this framework, the rate-quantization (R-Q) and distortion-quantization (D-Q) functions (collectively called R-D functions in this work) of the video encoder can be accurately estimated with very low computational complexity before quantization and coding. With the accurate estimation of the R-Q function, a frame-level rate control algorithm is proposed for DCT video coding. The proposed algorithm outperforms the TMN8 rate control algorithm by providing more accurate and robust rate regulation and better picture quality. Based on the estimated R-D functions, an encoder-based rate-shape-smoothing algorithm is proposed. With this smoothing algorithm, the output bit stream of the encoder has both a smoothed rate shape and a consistent picture quality, which are highly desirable in practical video coding and transmission.

Generalized multiple description coding with correlating transforms

Abstract: Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptions; thus, MD coding is suitable for packet erasure channels or networks without priority provisions. Generalizing work by Orchard, Wang, Vaishampayan and Reibman (see Proc IEEE Int. Conf. Image Processing, vol.I, Santa Barbara, CA, p.608-11, 1997), a transform-based approach is developed for producing M descriptions of an N-tuple source, M/spl les/N. The descriptions are sets of transform coefficients, and the transform coefficients of different descriptions are correlated so that missing coefficients can be estimated. Several transform optimization results are presented for memoryless Gaussian sources, including a complete solution of the N=2, M=2 case with arbitrary weighting of the descriptions. The technique is effective only when independent components of the source have differing variances. Numerical studies show that this method performs well at low redundancies, as compared to uniform MD scalar quantization.

A unified rate-distortion analysis framework for transform coding

Abstract: In our previous work, we have developed a rate-distortion (R-D) modeling framework for H.263 video coding by introducing the new concepts of characteristic rate curves and rate curve decomposition. In this paper, we further show it is a unified R-D analysis framework for all typical image/video transform coding systems, such as embedded zero-tree wavelet (EZW), set partitioning in hierarchical trees (SPIHT) and JPEG image coding; MPEG-2, H.263, and MPEG-4 video coding. Based on this framework, a unified R-D estimation and control algorithm is proposed for all typical transform coding systems. We have also provided a theoretical justification for the unique properties of the characteristic rate curves. A linear rate regulation scheme is designed to further improve the estimation accuracy and robustness, as well as to reduce the computational complexity of the R-D estimation algorithm. Our extensive experimental results show that with the proposed algorithm, we can accurately estimate the R-D functions and robustly control the output bit rate or picture quality of the image/video encoder.

Three-dimensional lifting schemes for motion compensated video compression

Abstract: Three-dimensional wavelet decompositions are efficient tools for scalable video coding. We show a lifting formulation for these decompositions. The temporal wavelet transform is inherently nonlinear, due to the motion estimation step, and the lifting formalism allows us to provide several improvements to the scheme initially proposed by Choi and Woods: a better processing of the uncovered areas is proposed and an overlapped motion-compensated temporal filtering method is introduced in the multiresolution decomposition. As shown by simulations, the proposed method results in higher coding efficiency, while keeping the scalability functionalities.

Edge-directed prediction for lossless compression of natural images

Abstract: This paper sheds light on the least-square (LS)-based adaptive prediction schemes for lossless compression of natural images. Our analysis shows that the superiority of the LS-based adaptation is due to its edge-directed property, which enables the predictor to adapt reasonably well from smooth regions to edge areas. Recognizing that LS-based adaptation improves the prediction mainly around the edge areas, we propose a novel approach to reduce its computational complexity with negligible performance sacrifice. The lossless image coder built upon the new prediction scheme has achieved noticeably better performance than the state-of-the-art coder CALIC with moderately increased computational complexity.

Video coding for streaming media delivery on the Internet

Abstract: We provide an overview of an architecture of today's Internet streaming media delivery networks and describe various problems that such systems pose with regard to video coding. We demonstrate that based on the distribution model (live or on-demand), the type of the network delivery mechanism (unicast versus multicast), and optimization criteria associated with particular segments of the network (e.g., minimization of distortion for a given connection rate, minimization of traffic in the dedicated delivery network, etc.), it is possible to identify several models of communication that may require different treatment from both source and channel coding perspectives. We explain how some of these problems can be addressed using a conventional framework of temporal motion-compensated, transform-based video compression algorithm, supported by appropriate channel-adaptation mechanisms in client and server components of a streaming media system. Most of these techniques have already been implemented in RealNetworks(R) RealSystem(R) 8 and its RealVideo(R) 8 codec, which we use throughout the paper to illustrate our results.

Motion-compensated highly scalable video compression using an adaptive 3D wavelet transform based on lifting

Abstract: This paper proposes a new framework for the construction of motion compensated wavelet transforms, with application to efficient highly scalable video compression. Motion compensated transform techniques, as distinct from motion compensated predictive coding, represent a key tool in the development of highly scalable video compression algorithms. The proposed framework overcomes a variety of limitations exhibited by existing approaches. This new method overcomes the failure of frame warping techniques to preserve perfect reconstruction when tracking complex scene motion. It also overcomes some of the limitations of block displacement methods. Specifically, the lifting framework allows the transform to exploit inter-frame redundancy without any dependence on the model selected for estimating and representing motion. A preliminary implementation of the proposed approach was tested in the context of a scalable video compression system, yielding PSNR performance competitive with other results reported in the literature.

Video-on-demand broadcasting protocols: a comprehensive study

Abstract: Broadcasting protocols are proved to be efficient for transmitting most of the popular videos in video-on-demand systems. We propose a generalized analytical approach to evaluate the efficiency of the broadcasting protocols and derive the theoretical lower bandwidth requirement bound for any periodic broadcasting protocols. By means of the proposed analytical tool-temporal-bandwidth map, the approach can be used to direct the design of periodic broadcasting protocols to achieve different goals, e.g., server bandwidth requirement, client waiting time, client I/O bandwidth requirement etc. As the most important performance index in a VOD system is the required server bandwidth, we give the solution to achieve the optimal bandwidth efficiency given client waiting time requirement and the length of the video. To take into account the popular compressed video with variable bit rate, the optimal approach is applied readily to the VBR videos and can achieve zero loss and best bandwidth efficiency. We give a proof why existing techniques such as smoothing and prefetching is not necessary and in some cases inefficient in broadcasting protocols. We also discuss how broadcasting schemes can be tailored to support true and interactive VOD service. An insightful comparison between broadcasting and multicasting schemes is also given.

Wavelets, approximation, and compression

Abstract: Over the last decade or so, wavelets have had a growing impact on signal processing theory and practice, both because of the unifying role and their successes in applications. Filter banks, which lie at the heart of wavelet-based algorithms, have become standard signal processing operators, used routinely in applications ranging from compression to modems. The contributions of wavelets have often been in the subtle interplay between discrete-time and continuous-time signal processing. The purpose of this article is to look at wavelet advances from a signal processing perspective. In particular, approximation results are reviewed, and the implication on compression algorithms is discussed. New constructions and open problems are also addressed.

Frequency-directed run-length (FDR) codes with application to system-on-a-chip test data compression

Abstract: We showed recently that Golomb codes can be used for efficiently compressing system-on-a-chip test data. We now present a new class of variable-to-variable-length compression codes that are designed using the distributions of the runs of 0s in typical test sequences. We refer to these as frequency-directed run-length (FDR) codes. We present experimental results for the ISCAS 89 benchmark circuits to show that FDR codes outperform Golomb codes for test data compression. We also present a decompression architecture for FDR codes, and an analytical characterization of the amount of compression that can be expected using these codes. Analytical results show that FDR codes are robust, i.e. they are insensitive to variations in the input data stream.

Aerial video surveillance and exploitation

Abstract: There is growing interest in performing aerial surveillance using video cameras. Compared to traditional framing cameras, video cameras provide the capability to observe ongoing activity within a scene and to automatically control the camera to track the activity. However, the high data rates and relatively small field of view of video cameras present new technical challenges that must be overcome before such cameras can be widely used. In this paper, we present a framework and details of the key components for real-time, automatic exploitation of aerial video for surveillance applications. The framework involves separating an aerial video into the natural components corresponding to the scene. Three major components of the scene are the static background geometry, moving objects, and appearance of the static and dynamic components of the scene. In order to delineate videos into these scene components, we have developed real time, image-processing techniques for 2-D/3-D frame-to-frame alignment, change detection, camera control, and tracking of independently moving objects in cluttered scenes. The geo-location of video and tracked objects is estimated by registration of the video to controlled reference imagery, elevation maps, and site models. Finally static, dynamic and reprojected mosaics may be constructed for compression, enhanced visualization, and mapping applications.

Compressing XML with multiplexed hierarchical PPM models

Abstract: We established a working Extensible Markup Language (XML) compression benchmark based on text compression, and found that bzip2 compresses XML best, albeit more slowly than gzip. Our experiments verified that T/sub XMILL/ speeds up and improves compression using gzip and bounded-context PPM by up to 15%, but found that it worsens the compression for bzip2 and PPM. We describe alternative approaches to XML compression that illustrate other tradeoffs between speed and effectiveness. We describe experiments using several text compressors and XMILL to compress a variety of XML documents. Using these as a benchmark, we describe our two main results: an online binary encoding for XML called Encoded SAX (ESAX) that compresses better and faster than existing methods; and an online, adaptive, XML-conscious encoding based on prediction by partial match (PPM) called multiplexed hierarchical modeling (MHM) that compresses up to 35 % better than any existing method but is fairly slow.

Compression and transmission of depth maps for image-based rendering

Abstract: We consider applications using depth-based image-based rendering (IBR), where the synthesis of arbitrary views occur at a remote location, necessitating the compression and transmission of depth maps. Traditional image compression has been designed to provide maximum perceived visual quality, and a direct application is sub-optimal for depth-map compression, since depth-maps are not directly viewed. In other words, the sensitivity of the rendering error depends on the image content as well as on the depth map, we propose two improvements to take this into account. Firstly, we consider region-of-interest (ROI) coding, where we identify those regions of the image where accurate depth is most crucial. Secondly, we reshape the dynamic range of the depth map. Our experiments show a significant improvement in coding gain (1.1 dB) and rendering quality when we integrated these two improvements into a standard JPEG-2000 coder.

System and method for incremental and continuous data compression

Abstract: A data compression system and method for that is capable of detecting and eliminating repeated phrases of variable length within a window of virtually unlimited size.

Invertible authentication watermark for JPEG images

Abstract: We present two new invertible watermarking methods for authentication of digital images in the JPEG format. While virtually all previous authentication watermarking schemes introduced some small amount of non-invertible distortion in the image, the new methods are invertible in the sense that, if the image is deemed authentic, the distortion due to authentication can be completely removed to obtain the original image data. The first technique is based on lossless compression of biased bit-streams derived from the quantized JPEG coefficients. The second technique modifies the quantization matrix to enable lossless embedding of one bit per DCT coefficient. Both techniques are fast and can be used for general distortion-free (invertible) data embedding. The new methods provide new information assurance tools for integrity protection of sensitive imagery, such as medical images or high-importance military images viewed under non-standard conditions when usual criteria for visibility do not apply.

Coding for the Slepian-Wolf problem with turbo codes

Abstract: This paper proposes a practical coding scheme for the Slepian-Wolf problem of separate encoding of correlated sources. Finite-state machine (FSM) encoders, concatenated in parallel, are used at the transmit side and an iterative turbo decoder is applied at the receiver. Simulation results of system performance are presented for binary sources with different amounts of correlation. Obtained results show that the proposed technique outperforms by far both an equivalent uncoded system and a system coded with traditional (non-concatenated) FSM coding.

ECG data compression using truncated singular value decomposition

Abstract: The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal information is mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that the truncated SVD method can provide efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission.