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A geometry-based image compression method-non-uniform light field compression is proposed by combining bi-triangle-based surface light field partition and non-uniform factoring of light field matrix, through which a four orders magnitude compression ratio can be achieved. Starting from dense images captured from vantage points, the codec resample these original data and partition the resampled data over bi-triangle. Then the codec arrange these partitioned light field data into 2D matrices and approximate the matrices through factoring them into non-uniform textures. Finally the codec group these textures into tiles and further compress these textures using ordinary still image compression techniques. Novel image can be rendered in real-time through texture mapping. In this paper we illustrate the compression efficiency and rendering performance through dense images captured in real scene.

Data compression is the process of changing data into a smaller form from which the original can be recovered at a later date. It is vital because of the increased use of data compression in commercial, scientific and statistical information systems, and communications networks. Today, data compression has become a crucial component and its main goal of hardware compression systems is to achieve high performance at low costs with low power consumption. There are five steps to the encoding algorithm and six steps to the decoding algorithm. The compression methods used depend on the type of data that is used, such as text, graphics, image, audio, or video, which together represent the multimedia information. This chapter further illustrates the information available on lossless and lossy compression hardware. The establishment of standards made it possible to design and develop special-purpose architectures and application-specific VLSI systems to implement sophisticated compression techniques that can process in real time. Image compression is critical in large image databases as well as in applications where images are transferred over the network. Lossless images are especially important in medical and space applications. Image compression methods are computationally intensive and ideal examples for hardware implementation. In recent years, video communication has become an essential part of a wide range of applications, therefore cheap digital storage media and numerous digital transmission channels have triggered a huge growth in video communication.

Presents DGPSL (distributed graphics processing support library) which is one of major components of the authors' distributed graphics processing support environment. It is a facility for implementing graphics applications which require expensive computing power that is not available on single workstation. The paper describes in detail the techniques in designing and implementing DGPSL. >

In a multimedia system, one is required to handle, store and transmit a lot of data. We consider lossless data compression proposed by Lempel and Ziv (1977). We review the various methods and techniques of improving the compression ratio of the LZ77 scheme, and write a compression program to get a 3.14 times compression for various file styles by using these methods. In English text, the LZ77 optimal algorithms of LZ77 can achieve a compression efficiency of about 2.5 bits per character, however the entropy of English text is about 1.3 bits per character, so we can compress the data further. Another way of improving compression ratio is by arithmetic coding.

We present an algorithm for text compression. The basic idea of our algorithm is to define a unique encryption or signature of each word in the dictionary by replacing certain characters in the words by a special character "*" and retaining a few characters so that the word is still retrievable. For any encrypted text the most frequently used character is "*" and the standard compression algorithms can exploit this redundancy in an effective way. We advocate the following compression paradigm: given a compression algorithm A and a text T, we apply the same algorithm A on an encrypted text *T and retrieve the original text via a dictionary which maps the decompressed text *T to the original text T. We report better results for most widely used compression algorithms such as Huffman, LZW, arithmetic, unix compress, gnu-zip with respect to a text corpus. The compression rates using these algorithms are much better than the dictionary based methods reported in the literature. One basic assumption of our algorithm is that the system has access to a dictionary of words used in all the texts along with a corresponding "cryptic" dictionary. The cost of this dictionary is amortized over the compression savings for all the text files handled by the organization. If two organizations wish to exchange information using our compression algorithm, they must share a common dictionary. We compare our methods with other dictionary based methods and present future research problems.

The authors have explored the particular needs of large information retrieval systems, in which hundreds of megabytes of data are stored, retrieval is non-sequential, and new text is continually being appended. It has been shown that the word-based model can be adapted to cope well both with dynamic environments, and with situations in which decode-time memory is limited. In the latter case as little as 100 Kb of main memory is sufficient to achieve excellent compression, provided a suitable choice of tokens is used as the compression lexicon. To solve the former problem a new paradigm of compression has been introduced, in which some components of the compression model are required to remain static to ensure that all parts of the text can be decoded, and some parts are extensible, so that new text can also influence the assignment of codewords. An additional heuristic-Swap-to-Near-the-Front-allows collections to be seeded with as little as 1/1000 of their final text with minimal loss of compression efficiency. The resulting "almost static" compression method is ideal for large dynamic collections. >

Storing full motion graphics animation or television images in a Personal Computer will generate huge amounts of data which will soon overwhelm even very large disc drives. Storing or retrieving images from a disc at 30 frames per second speed is not yet possible. The now common JPEG image compression standard can offer some relief at the price of generating more and more image distortions and visual artifacts with increased compression. A new "Lossless" image compression scheme, based on Autosophy networks, has been implemented and tested in an IBM PC (486). The algorithms operate by constructing pyramidal cascades of image fragments in a mathematical Omni Dimensional Hyperspace library which is stored in a disc file. Each image fragment of any size is stored only once to be reused and recycled in subsequent image storage. This will lead to saturation in the storage requirement in which the more images that have already been stored the less additional storage space is required to store additional images. The storage requirement for graphics images becomes totally independent of the image size, image resolution or the number of frames to be stored. Storage requirement only depends on the "Novelty" within the images or how similar the frames are to each other. Experimental data confirms the algorithms and suggests a highly superior method for storing images in PCs. But, real live animation or on-screen teleconferencing is only possible with specialized new graphics boards, which are slightly larger and slightly more expensive than conventional graphics boards. >

The JPEG (Joint Photographic Experts Group) algorithm is the international standard for still image compression and has already been implemented in some video display systems and color scanners. An extension to JPEG, known as JPEG/sup ++/, allows a far greater range of compression and quality options for graphics users. To complete the implementation of compression in the graphics production chain, JPEG will be implemented in color printers. The authors provide an overview of the JPEG compression standard and the JPEG/sup ++/ extension and discuss their application to high-quality color desktop publishing. >

In this work a dedicated pipeline for real time image compression, aimed at document archiving purposes, is described. Page segmentation is performed prior to compression in order to apply different compression methods to picture and text areas, considerably increasing the overall compression ratio. Page analysis and compression algorithms, suitable for implementation on reconfigurable hardware systems, are described.

A current technique to control the rendering speed in interactive virtual worlds is the representation of object geometry using a hierarchical level of detail. Missing features can be supplied through the use of texture maps, but the reduced rendering time is bought at a trade-off in the amount of memory required to store the texture images. Compressed texturing techniques (e.g. S3TC, FTX1, VQ) offer some relief, but at a cost to image quality and detail. This paper proposes a solution using texture images compressed with JPEG2000. The foveated JPEG2000 texture mapping method (fJ2k) decompresses codestreams to resolutions that vary based on current rendering performance and position of the requested texture image in the field of view. The final result is a foveated viewport rendered at interactive frame rates using significantly less memory than current methods.

Many polygon meshes have properties such as shading normals, colours, texture coordinates, and/or material attributes that are associated with the vertices, faces or corners of the mesh. While current research in mesh compression has focused on connectivity and geometry coding, the compression of properties has received less attention. There are two kinds of information to compress. One specifies each individual property: the property values. The other describes how the properties are attached to the mesh: the property mapping. The authors introduce a predictive compression scheme for the property mapping that is 2 to 10 times more compact than previously reported methods.

Recently, more advanced image quality and many techniques are needed in 3D computer graphics. Especially texture mapping support is the major issue in the design of high performance 3D graphics system. In this paper, a high-performance 3D graphics hardware is designed for texture mapping. The proposed system is composed of a single-chip rasterizer and frame buffer using a processor-memory integration method, which is adapted for processing high-performance 3D graphics. Also, the texture mapping unit is designed using the processor-memory integration technology to provide sufficient bandwidth. Therefore, the tremendous memory bandwidth and the long latency required for texture mapping can be reduced by this approach.

The performance of VLSI graphics processors is rising rapidly with the incorporation of specialized 3D geometry processing hardware into the graphics accelerator. Due to memory and bus bandwidth limitations, host systems often cannot deliver geometric data to graphics processors fast enough to saturate their processing capability. This paper proposes a compression scheme designed to alleviate the bandwidth bottleneck by transmitting triangle meshes to the graphics engine as an instruction stream. Controlling a vertex cache within the graphics subsystem allows redundant vertex transmissions and thus transformations to be virtually eliminated. The non-vertex bandwidth overhead is approximately 2-4 bits/triangle, which is less than half the overhead of competing techniques.

The growing number of applications for 3D graphics and imaging systems in the mass market requires the customized approach to the design of high-performance 3D graphics and imaging system architectures. That fact coupled with the strong trends to industrial standardization of graphics API, such as OpenGL, leads to enhanced portability for imaging and graphics applications. The progress on the hardware support of API functionality gives a real possibility to use a top-down approach in the design of custom graphics/imaging systems based on the mixed hardware/software implementation of the OpenGL architecture. Software simulation is a relatively cheap and fast way for initial graphics architecture template development and evaluation to acquire the structure and parameters that can be used later for HDL elaboration and simulation. This paper discusses a 3D graphics and imaging system architecture model implementation based on OpenGL API hardware support simulation. The object-oriented approach has been used for this development of analytic and software models simulating hardware units on different stages of the graphics pipeline. The Interactive Imaging System Architecture Composer has been developed in this project for fast run-time simulation management, data acquisition and interpretation. The expandable set of architecture templates uses a reconfigurable shared library of "virtual hardware units" simulating the different hardware structures for graphics and image processing.

The processing of colored documents with Document Management Systems (DMS) is possible with the modern document scanning systems today. Because of the enormous amount of image data generated scanning a typical A4 document with a 300 dpi resolution, image compression is used. The JPEG compression scheme is widely used for such image data. The lack of image quality caused by necessary lossy compression, can significantly reduce the recognition quality of a subsequent optical character recognition (OCR) process, which is essential to any DMS system. The new standard JPEG2000 (Part 6), a high performance system for compressing and archiving scanned documents, particularly those containing text and image, is overcoming the gap between high compression and legibility of documents suitable to be managed inside DMS systems. The utilization of JPEG2000 (Part 6) results in substantially higher image quality in comparison to standard compression techniques. This high quality is achieved by combining automatic text detection with bitonal compression of text and color/grayscale wavelet compression of images. Since the innovative JPEG2000 (Part 6) compression scheme is a complex image processing system, allocating some computational performance, a scalable software system has been designed to meet the throughput of high-performance document scanners.

The architecture for block-based video applications (e.g. MPEG/JPEG coding, graphics rendering) is usually based on a processor engine, connected to an external background SDRAM memory where reference images and data are stored. In this paper, we reduce the required memory bandwidth for MPEG coding up to 67% by identifying the optimal block configuration and applying embedded data compression up to a factor four. It is shown that independent compression of fixed-sized data blocks with a fixed compression ratio can decrease the memory bandwidth for a limited set of compression factors only. To achieve this result, we exploit the statistical properties of the burst-oriented data exchange to memory. It has been found that embedded compression is particularly attractive for bandwidth reduction when a compression ratio 2 or 4 is chosen. This moderate compression factor can be obtained with a low-cost compression scheme such as DPCM with a small acceptable loss of quality.

Data compression is one of key techniques in image processing. To begin with, this paper discusses the actuality of image compression coding, and then introduces generalized computing concept. Finally, by introducing knowledge to date compression, this paper presents a kind of intelligent image compression model (IICM) based on generalized computing.

We review some of our recent work on LZ-based, single-pass, adaptive algorithms for the compression of digital images. Our approach combines dictionary techniques from adaptive lossless text compression with quantization techniques to obtain single-pass, highly adaptive compression algorithms that allow the compression-fidelity tradeoff to be continuously adjusted, and lend themselves to high-speed parallel/hardware implementation.

In this paper a technique is presented that combines interactive hardware accelerated bump mapping with shift-variant anisotropic reflectance models. An evolutionary path is shown how some simpler reflectance models can be rendered at interactive rates on current low-end graphics hardware, and how features from future graphics hardware can be exploited for more complex models.We show how our method can be applied to some well known reflectance models, namely the Banks model, Ward's model, and an anisotropic version of the Blinn-Phong model, but it is not limited to these models.Furthermore, we take a close look at the necessary capabilities of the graphics hardware, identifiy problems with current hardware, and discuss possible enhancements.

Recent developments show that it is possible to implement drivers using 3D Graphics Hardware for the PC, which obtain performance previously found only in very expensive, specialized graphics systems. Typically, these drivers provide single application support only. This unfortunately results in the lack of having the comfort of a Windowing System and the inability to output to more than one viewing window. In this paper, an implementation to include the missing properties is discussed.

The realization of new MPEG-4 functionality, applicable to 3D graphics texture compression and image database access over the Internet, is demonstrated in a PC-based compression system. Applying our system-level design methodologies effectively removes all implementation bottlenecks. A first-of-a-kind ASIC, called Ozone, accelerates the Embedded Zero Tree based encoding and is capable of compressing 30 color CIF images per second.

We describe a color image compression and decompression scheme suitable for high resolution printers. The proposed scheme requires only two image rows in memory at any time, and hence is suitable for low-cost, high-resolution printing systems. The compression ratio can be specified and is achieved exactly. Compound document images consisting of continuous-tone, natural regions mixed with synthetic graphics or text are handled with uniformly high quality. While the target compression ratios are moderate, the quality requirements are extremely high: the compressed and decompressed printed image needs to be virtually indistinguishable from the original printed image. The scheme combines a lossless block coding technique with a wavelet block codec. The wavelet block codec uses a new and simple entropy coding technique that is more suitable for the specific block-structure, compression target, and discrete wavelet transform used.

Summary form only given. Current adaptive compression schemes such as GZIP and COMPRESS are impractical for database compression as they do not allow random access to individual records. A compression algorithm for general-purpose database systems must address the problem of randomly accessing and individually decompressing records, while maintaining compact storage of data. The SEQUITUR algorithm of Nevill-Manning et al., (1994, 1996, 1997) also adaptively compresses data, achieving excellent compression but with significant main-memory requirements. A preliminary version of SEQUITUR used a semi-static modelling approach to achieve slightly worse compression than the adaptive approach. We describe a new variant of the semi-static SEQUITUR algorithm, RAY, that reduces main-memory use and allows random-access to databases. RAY models repetition in sequences by progressively constructing a hierarchical grammar with multiple passes through the data. The multiple pass approach of RAY uses statistics on character pair repetition, or digram frequency, to create rules in the grammar. While our preliminary implementation is not especially fast, the multi-pass approach permits reductions in compression time, at the cost of affecting compression performance, by limiting the number of passes. We have found that RAY has practicable main-memory requirements and achieves better compression than an efficient Huffmann scheme and popular adaptive compression techniques. Moreover, our scheme allows random access to data and is not restricted to databases of text.

Previous works have proposed adding compression techniques to a variety of architectural styles to reduce instruction memory requirements. It is not immediately clear how these results apply to DSP architectures. DSP instructions are longer and have potentially greater variation which can decrease compression ratio. Our results demonstrate that DSP programs do provide sufficient repetition for compression algorithms. We propose a compression method and apply it to SHARC, a popular DSP architecture. Even using a very simple compression algorithm, it is possible to halve the size of the instruction memory requirements.

The work has set out to investigate the application of data compression on real-time images used in shape measurement and machine vision applications. The quality of monochromatic images produced from compression based on the lossless schemes and DCT transform were analyzed for their degradation level. The lossy based DCT method appeared to provide the higher compression ratio of 6:1 required. Special concern was focused into the fringe pattern analysis area, whereby how the degraded compressed fringe images could possibly effect the accuracy of its application output. The real-time image compression mechanism is anticipated for a seamless transmission to a personal computer, through a standard interface channel.

The diversity in TV images has augmented with the increased application of computer graphics. In this paper we study z coding system that supports both the lossless coding of such graphics data and regular lossy video compression. The lossless coding techniques are based on runlength and arithmetical coding. For video compression, we introduce a simple block predictive coding technique featuring individual pixel access, so that it enables a gradual shift from lossless coding of graphics to the lossy coding of video. An overall bit rate control completes the system. Computer simulations show a very high quality with a compression factor between 2-3.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

It has become increasingly difficult to drive a modern highperformance graphics accelerator at full speed with a serial immediate-mode graphics interface. To resolve this problem, retainedmode constructs have been integrated into graphics interfaces. While retained-mode constructs provide a good solution in many cases, at times they provide an undesirable interface model for the application programmer, and in some cases they do not solve the performance problem. In order to resolve some of these cases, we present a parallel graphics interface that may be used in conjunction with the existing API as a new paradigm for highperformance graphics applications. The parallel API extends existing ideas found in OpenGL and X11 that allow multiple graphics contexts to simultaneously draw into the same image. Through the introduction of synchronization primitives, the parallel API allows parallel traversal of an explicitly ordered scene. We give code examples which demonstrate how the API can be used to expose parallelism while retaining many of the desirable features of serial immediate-mode programming. The viability of the API is demonstrated by the performance of our implementation which achieves scalable performance on a 24 processor system. CR

In this paper we introduce a new compressed representation for the connectivity of a triangle mesh. We present local compression and decompression algorithms which are fast enough for real time applications. The achieved space compression rates keep pace with the best rates reported for any known global compression algorithm. These nice properties have great benefits for several important applications. Naturally, the technique can be used to compress triangle meshes without significant delay before they are stored on external devices or transmitted over a network. The presented decompression algorithm is very simple allowing a possible hardware realization of the decompression algorithm which could significantly increase the rendering speed of pipelined graphics hardware. CR Categories: I.3.1 [Computer Graphics]: Hardware Architecture; I.3.3 [Computer Graphics]: Picture/Image Generation— Display algorithms

Compression in the context of texture and bump mapping brings high-performance texture mapping in the range of low- cost systems. The size for the texture memory is significantly reduced and the necessary bandwidth between the memory and texturing unit is lowered. Textures are compressed using a lossy compression method based on vector quantization. We are proposing an alternative approach to embossing textured surfaces, where bump maps are described with bitmaps and are part of the compressed texture data. The design of a texturing circuit architecture is presented, where embossing or engraving of textured surfaces is executed by dedicated decoding and filtering hardware. The circuit decompresses textures and decodes compressed bump maps to produce wrinkled textured surfaces. Applying encoding to normal vectors results in narrower data paths. Vectors are represented and handled in a compressed format defined by their vertical and horizontal angles. In order to enhance subjective image quality, an optional space-variant filter can be applied locally during the texture mapping phase to reduce the artifacts introduced by the lossy compression method.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Summary form only given. We discuss the use of a new algorithm to preprocess text in order to improve the compression ratio of textual documents, in particular online documents such as web pages on the World Wide Web. The algorithm was first introduced in an earlier paper, and in this paper we discuss the applicability of our algorithm in Internet and Intranet environments, and present additional performance measurements regarding compression ratios, memory requirements and run time. Our results show that our preprocessing algorithm usually leads to a significantly improved compression ratio. Our algorithm requires a static dictionary shared by the compressor and the decompressor. The basic idea of the algorithm is to define a unique encryption or signature for each word in the dictionary, and to replace each word in the input text by its signature. Each signature consists mostly of the special character '*' plus as many alphabetic characters as necessary to make the signature unique among all words of the same length in the dictionary. In the resulting cryptic text the most frequently used character is typically the '*' character, and standard compression algorithms like LZW applied to the cryptic text can exploit this redundancy in order to achieve better compression ratios. We compared the performance of our algorithm to other text compression algorithms, including standard compression algorithms such as gzip, Unix 'compress' and PPM, and to one text compression algorithm which uses a static dictionary.

D graphics transform 3D models into 2D images by simulating the physics of light propagation from the lighting sources, through the objects, and eventually to the eyes. Although specialized graphics hardware engines have been proposed and implemented in the past, and a heated in- terest in PC-class 3D graphics cards is currently emerging, detailed descriptions and analysis of 3D graphics workloads which graphics hardware design can be based on are almost non-existent. This work takes the first step towards a compre- hensive 3D graphics workload characterization by reporting the results of an empirical study us- ing an instrumented software polygonal renderer tested on a wide variety of static 3D graphics models with sufficiently sophisticated geometric and texture properties.

The OpcnGL Graphics System provides a well-specified, widelyaccepted dataflow for 3D graphics and imaging. OpenGL is an UTclrirechaa; nn OpenGL-capable computer is a hardware manifestation or ir,~plenrentution of that architecture. The Onyx2 InfiniteReality nnd 02 workstations exemplify two very different implementntions of OpenGL. The hvo designs respond to different cost, performance, and capability goals. Common practice is to describe a graphics hardware implementntion bnscd on how the hardware itself operates. However, this pnper discusses hvo OpenGL hardware implementations based on how they embody the OpenGL architecture. An important thread throughout is how OpenGL implementations can be designed not merely based on gmphics price-performance considerations, but nlso with considemtion of larger system issues such as memory architecture, compression, and video processing. Just as OpenGL is influenced by wider system concerns, OpenGL itself can provide a clarifying influence on system capabilities not conventionally thought of as graphics-related. CR Categories: 1.3.1 [Computer Graphics]: Hardware Architecture; 1.3.6 [Computer Graphics]: Methodology and TechniquesStandards

Data compression is very necessary in business data processing, because of the cost savings that it offers and the large volume of data manipulated in many business applications. It is a method or system for transmitting a digital image (i.e., an array of pixels) from a digital data source to a digital data receiver. More the size of the data be smaller, it provides better transmission speed and saves time. In this communication, we always want to transmit data efficiently and noise freely. This paper will provide some compression techniques for lossless text type data compression and comparative result of multiple and single compression, that will help to find out better compression output and to develop compression algorithms.

The diversity in the nature of TV images is increasing due to the mixing of graphics data with natural scenery. In this paper we study the lossless coding of such graphics data with the objective to come to recommendations for video compression of such images. For this purpose, a comparison has been made between contour coding, template coding and run-length coding of graphical imagery. It is concluded that template coding is suitable for TXT-like images but it is not practical for more generic graphics images. For menus and similar imagery, contour and run-length coding provide interesting options.

We present a simple method for rendering directly from compressed textures in hardware and software rendering systems. Textures are compressed using a vector quantization (VQ) method. The advantage of VQ over other compression techniques is that textures can be decompressed quickly during rendering. The drawback of using lossy compression schemes such as VQ for textures is that such methods introduce errors into the textures. We discuss techniques for controlling these losses. We also describe an extension to the basic VQ technique for compressing mipmaps. We have observed compression rates of up to 35 : 1, with minimal loss in visual quality and a small impact on rendering time. The simplicity of our technique lends itself to an efficient hardware implementation. CR categories: I.3.7 [Computer Graphics]: 3D Graphics and Realism Texture; I.4.2 [Image Processing]: Compression Coding

Publisher Summary There is an increasing use of multimedia computing techniques in a wide range of diverse application areas; for example, manufacturing and commerce, publishing, education, and leisure services. Central to these techniques is the processing, storage, and transmission of both still photographs and video sequences. It is well known that the volume of data required to describe such images in their raw form makes storage prohibitively expensive and greatly slows transmission. The aim of this chapter is to develop and implement new generic image compression methods, based on the use of wavelet transforms and vector quantization (VQ) techniques, to achieve very high compression results while maintaining satisfactory image quality. A major problem with current wavelet-based compression methods is the large amount of computation required to process a single image. This problem is exacerbated with the requirement to process video sequences in real-time. The chapter intends to use previously developed hardware/software co-design techniques to partition the compression and decompression algorithms between hardware and software implementations to maximize the compression performance at acceptable cost.

This paper presents a reconfigurable machine for applications in image or video compression. The machine can be used stand alone or as a universal accelerator co-processor for desktop computers for image processing. It is well suited for image compression algorithms such as JPEG for still pictures or for encoding MPEG movies. It provides a much cheaper and more flexible hardware platform than special image compression ASICs and it can substantially accelerate desktop computing.

Summary of Progress: Our work in this one-year project has been very successful. It has revolved around the following three important areas dealing data compression and its applications: (1) the design and analysis of sophisticated methods for prediction based on data compression techniques, with applications to prefetching, caching, and locality management; (2) fast, practical, and code-efficient implementations of arithmetic coding and other coding methods, for use in text and image compression; and (3) new methods for choosing motion vectors yielding substantially better rate-distortion tradeoffs for video compression in videoconferencing applications. (KAR) P. 2

Multimedia applications require a compression and decompression scheme for digital video. The standardized and widely used techniques JPEG and MPEG provide very good compression ratios, but are computationally quite complex and demanding. We propose to use an extension to the much simpler Color Cell Compression scheme as an alternative. Our extension includes the use of variable block sizes, the reuse of color index values from previously encoded blocks, and Huffman encoding of the stream of blocks. We present experimental results showing that our scheme provides much better runtime performance than MPEG, at the cost of a slightly inferior compression ratio. It is thus especially suited for software videos in high-speed networks.

We present a report on the effects of compressing stereo pairs using lossy compression techniques. We discuss the general functionality of all lossy compressors with particular emphasis on the CCITT/ISO JPEG Still Picture Compression Standard. We show that the application of lossy compressors to stereo pairs can cause ambiguities in the resulting stereo image and we develop a measure to quantify those ambiguities. We describe two new techniques which each help to decrease some of these anomalies. We also discuss the compression rates on some test images with and without the use of these new techniques.

Hardware 3D graphics accelerators will be ubiquitous in the new millennium. The great majority of 3D graphics programs will, almost exclusively, use scene graphs. Rarely will graphics programs use immediate mode-if at all-and then only for very special effects, and scene graphs will grow to support new modalities such as sound and haptics. Outrageous? Probably. Predicting the future is never easy. By looking at where we are today and analyzing technology trends, these predictions may seem even more outrageous, outrageously mundane. The author considers how graphics technologies, hardware and software, are evolving at exponential rates.

Rapid image decompression is crucial for many potential Navy and commercial users of the fractal image compression scheme. The focus of the work was the development of IFS algorithms and computer code for image compression, the refinement of algorithms and computer code for compressing color images and the development of wavelet methods for image compression. Our improvements in compression algorithm have shortened image compression times significantly. During this time period two papers were submitted for publication.

Fractals have a natural affinity with computer graphics, generating images of limitless complexity and providing the basis for a very efficient compression algorithm.

Blt-stones, pronounced "blit-stones" are a set of standard routines for interfacing application programs to graphics memories on personal computers. Blt stands for block transfer, and in computer graphics its most common use is combined with bit, as in bitbit. Blt-stones make color bitbits fast and easy to code. They provide both quantitative and qualitative information about graphics hardware performance, and they give insight into the architectures of graphics boards. They can be used to count the number of pixel-writes per secound, or to determine how many bytes of code are required to gain access to a board's memory. Blt-stones is a term coined by the authors to be a graphics analog to whetsones and dhrysones, performance measures for computer processing speeds.

A description is given of the Titan Graphics Supercomputer. The primary design philosophy was to have as little redundant hardware as possible and to make as much of the hardware available to compiled application code as possible. This led to a design with multiple parallel processors, each with an integer unit and a vector floating-point unit. The system provides 3D graphics and image processing, using the main processors for most computations. The graphics subsystem consists of only a frame buffer with rasterization (vector and triangle pixel drawing) support. The Titan architecture provides a very good balance of computation and graphics but to make it more competitive in graphics or imaging-intensive applications, a special-purpose accelerator also fits into the architecture. >

This paper describes the implementation of a data compression scheme for an interactive colour graphics terminal in which the storage requirement is reduced in comparison with a full 1:1 bit map system. The paper also discusses the effect of data compression on the system design. Compression is performed in software using a microprocessor, and decompression of the picture code into raster scan form is performed in real time by hardware. The technique allows complex graphics pictures to be displayed at low cost.

In this paper a modified version of a noninformation preserving coding technique known as block truncation coding (BTC)is used to code multilevel graphics. The method is based on-local binarization of nonoverlapping blocks in the graphics image such that the sample mean and sample variance in each block is preserved. BTC is easy to implement, does not require multiple passes through the data, does not degrade when compressing noisy images, and can be made relatively insensitive to channel errors. Examples of the coding technique are given and compared to other compression methods. This technique shows promise for coding 32-level (or 32-color) graphic images at data rates of about 1 bit/pel.

The term “graphics dynamics” is used in this paper to describe a capability which permits the application programmer to specify a relationship between various graphics input devices and aspects of the graphics output presentation. Subsequent use of the input devices results in continuous real-time changes to the picture. An experimental graphics system is described, in which a powerful programmer's interface to graphics dynamics was implemented. This interface appears suitable for use as an extension to any of the existing standards and standards proposals, including, CORE, GKS, and PHIGS.