The JPEG2000 still image compression standard

The development of standards (emerging and established) by the International Organization for Standardization (ISO), the International Telecommunications Union (ITU), and the International Electrotechnical Commission (IEC) for audio, image, and video, for both transmission and storage, has led to worldwide activity in developing hardware and software systems and products applicable to a number of diverse disciplines [7], [22], [23], [55], [56], [73]. Although the standards implicitly address the basic encoding operations, there is freedom and flexibility in the actual design and development of devices. This is because only the syntax and semantics of the bit stream for decoding are specified by standards, their main objective being the compatibility and interoperability among the systems (hardware/software) manufactured by different companies. There is, thus, much room for innovation and ingenuity. Since the mid 1980s, members from both the ITU and the ISO have been working together to establish a joint international standard for the compression of grayscale and color still images. This effort has been known as JPEG, the Join

JPEG2000 image coding system theory and applications

JPEG2000, the new standard for still image coding, provides a new framework and an integrated toolbox to better address increasing needs for compression. It offers a wide range of functionalities such as lossless and lossy coding, embedded lossy to lossless coding, progression by resolution and quality, high compression efficiency, error resilience and region-of-interest (ROI) coding. Comparative results have shown that JPEG2000 is indeed superior to established image compression standards. Overall, the JPEG2000 standard offers the richest set of features in a very efficient way and within a unified algorithm. The price of this is its additional complexity, but this should not be perceived as a disadvantage, as the technology evolves rapidly

Ongoing standardization efforts

The JPEG 2000 Suite provides a comprehensive overview of the baseline JPEG 2000 standard and its extensions. The first part of the book sets out the core coding system, additions to the standard and reference software. The second part discusses the successful deployment of JPEG 2000 in application domains such as video surveillance, digital cinema, digital television, medical imaging, defence imaging, security, geographic imaging and remote sensing, digital culture imaging and 3D graphics. The book also presents implementation strategies accompanied by existing software and hardware solutions. • Describes secure JPEG 2000 (JPSEC), interactivity protocols (JPIP), volumetric image data compression (JP3D) and image compression in wireless environments (JPWL), amongst others. • Uses a structure which allows for easy cross-reference with the components of the standard. • Sets out practical implementation examples and results. • Examines strategies for future image compression techniques, including Advanced Image Coding and JPEG XR. • Includes contributions from international specialists in industry and academia who have worked on the development of the JPEG 2000 standard. • Additional material can be found at www.jpeg.org. The JPEG 2000 Suite is an excellent introduction to the JPEG 2000 standard and is of great appeal to practising electronics engineers, researchers, and hardware and software developers using and developing image coding techniques. Graduate students taking courses on image compression, digital archiving, and data storage techniques will also find the book useful, as will graphic designers, artists, and decision makers in industries developing digital applications

The JPEG 2000 still image compression standard

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEC2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide features and functionalities that current standards can either not address efficiently or in many cases cannot address at all. Lossless and lossy compression, embedded lossy to lossless coding, progressive transmission by pixel accuracy and by resolution, robustness to the presence of bit-errors and region-of-interest coding, are some representative features. It is interesting to note that JPEG2000 is being designed to address the requirements of a diversity of applications, e.g. Internet, color facsimile, printing, scanning, digital photography, remote sensing, mobile applications, medical imagery, digital library and E-commerce

JPEG2000: The upcoming still image compression standard

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide functionality that current standards can either not address efficiently or not address at all

The Effect of Space-filling Curves on the Efficiency of Hand Gesture Recognition Based on sEMG Signals

Over the past few years, Deep learning (DL) has revolutionized the field of data analysis. Not only are the algorithmic paradigms changed, but also the performance in various classification and prediction tasks has been significantly improved with respect to the state-of-the-art, especially in the area of computer vision. The progress made in computer vision has produced a spillover in many other domains, such as biomedical engineering. Some recent works are directed towards surface electromyography (sEMG) based hand gesture recognition, often addressed as an image classification problem and solved using tools such as Convolutional Neural Networks (CNN). This paper extends our previous work on the application of the Hilbert space-filling curve for the generation of image representations from multi-electrode sEMG signals, by investigating how the Hilbert curve compares to the Peano- and Z-order space-filling curves. The proposed space-filling mapping methods are evaluated on a variety of network architectures and in some cases yield a classification improvement of at least 3%, when used to structure the inputs before feeding them into the original network architectures

The JPEG2000 still image coding system: An overview

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide features and functionalities that current standards can either not address efficiently or in many cases cannot address at all. Lossless and lossy compression, embedded lossy to lossless coding, progressive transmission by pixel accuracy and by resolution, robustness to the presence of bit-errors and region-of-interest coding, are some representative features. It is interesting to note that JPEG2000 is being designed to address the requirements of a diversity of applications, e.g. Internet, color facsimile, printing, scanning, digital photography, remote sensing, mobile applications, medical imagery, digital library and E-commerce

Autopilot spatially-adaptive active contour parameterization for medical image segmentation

In this work, a novel framework for automated, spatially-adaptive adjustment of active contour regularization and data fidelity parameters is proposed and applied for medical image segmentation. The proposed framework is tailored upon the isomorphism observed between these parameters and the eigenvalues of diffusion tensors. Since such eigenvalues reflect the diffusivity of edge regions, we embed this information in regularization and data fidelity parameters by means of entropy-based, spatially-adaptive `heatmaps'. The latter are able to repel an active contour from randomly directed edge regions and guide it towards structured ones. Experiments are conducted on endoscopic as well as mammographic images. The segmentation results demonstrate that the proposed framework bypasses iterations dedicated to false local minima associated with noise, artifacts and inhomogeneities, speeding up contour convergence, whereas it maintains a high segmentation quality

Low Power FPGA Implementations of 256-bit Luffa Hash Function

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