10,255 research outputs found

    Secure JPEG 2000 - JPSEC

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    The Joint Photographic Experts Group (JPEG) has recently rolled out a new still image coding standard called JPEG 2000. This standard integrates an efficient image compression scheme with functionalities required by multimedia applications, such as progressiveness up to lossless coding, region of interest coding, and error resiliency. Security is a concern in many applications, and therefore also a desired functionality. This paper provides readers with insights and examples of how to combine security solutions with JPEG 2000 compression. Tools for JPEG 2000 compressed image integrity, access control, and copyright protection are presented. They can be either applied to a JPEG 2000 codestream or directly integrated into the coding/decoding operations, resulting in a fully compliant JPEG 2000 image

    Comparative performance analysis of image compression by JPEG 2000: a case study on medical images

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    JPEG 2000 is a new and improved, image-coding standard developed for compression of images. JPEG 2000 is the state-of-the-art image-coding standard that resulted from the joint efforts of the International Standards Organization (ISO) and the International Telecommunications Union (ITU); JPEG in JPEG 2000 is an acronym for Joint Picture Experts Group. The new standard outperforms the older JPEG standard by approximately 2 dB of Peak Signal to Noise Ratio (PSNR) for several images across all compression ratios. Reasons behind JPEG 2000 is superior performance are the wavelet transform and Embedded Block Coding with Optimal Truncation (EBCOT). This study describes the performance comparison of JPEG 2000 against its predecessor JPEG, by evaluating image compressions for medical images. The present research further describes the most important parameters of this new standard in order to help resolve design tradeoffs

    Ongoing standardization efforts

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    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

    JPEG 2000 Encoding with Perceptual Distortion Control

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    An alternative approach has been devised for encoding image data in compliance with JPEG 2000, the most recent still-image data-compression standard of the Joint Photographic Experts Group. Heretofore, JPEG 2000 encoding has been implemented by several related schemes classified as rate-based distortion-minimization encoding. In each of these schemes, the end user specifies a desired bit rate and the encoding algorithm strives to attain that rate while minimizing a mean squared error (MSE). While rate-based distortion minimization is appropriate for transmitting data over a limited-bandwidth channel, it is not the best approach for applications in which the perceptual quality of reconstructed images is a major consideration. A better approach for such applications is the present alternative one, denoted perceptual distortion control, in which the encoding algorithm strives to compress data to the lowest bit rate that yields at least a specified level of perceptual image quality. Some additional background information on JPEG 2000 is prerequisite to a meaningful summary of JPEG encoding with perceptual distortion control. The JPEG 2000 encoding process includes two subprocesses known as tier-1 and tier-2 coding. In order to minimize the MSE for the desired bit rate, a rate-distortion- optimization subprocess is introduced between the tier-1 and tier-2 subprocesses. In tier-1 coding, each coding block is independently bit-plane coded from the most-significant-bit (MSB) plane to the least-significant-bit (LSB) plane, using three coding passes (except for the MSB plane, which is coded using only one "clean up" coding pass). For M bit planes, this subprocess involves a total number of (3M - 2) coding passes. An embedded bit stream is then generated for each coding block. Information on the reduction in distortion and the increase in the bit rate associated with each coding pass is collected. This information is then used in a rate-control procedure to determine the contribution of each coding block to the output compressed bit stream

    JPEG privacy and security framework for social networking and GLAM services

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    Current image coding standards provide limited support for privacy and security features. An exception is the JPSEC standard, which defines security extensions in JPEG 2000 specifications (part 8). Notwithstanding this shortcoming, the JPEG committee is currently defining a new JPEG Systems standard, which envisages privacy and security support across JPEG family of standards. In this manuscript, the main philosophy of this emerging specification is outlined along with typical use cases, main requirements as well as examples of potential technological solutions. The upcoming specification guarantees backward and forward compatibility with earlier standards and legacy implementations. Finally, we illustrate the introduced framework by two applications targeting secure photo sharing on social networks and IPR management in the GLAM sector.Peer ReviewedPostprint (published version

    The JPEG XR Image Coding Standard

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    JPEG XR is the newest image coding standard from the JPEG committee. It primarily targets the representation of continuous-tone still images such as photographic images, and achieves high image quality, on par with JPEG 2000, while requiring low computational resources and storage capacity. Moreover, it effectively addresses the needs of emerging high dynamic range imagery applications by including support for a wide range of image representation format

    Image Compression using Discrete Cosine Transform & Discrete Wavelet Transform

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    Image Compression addresses the problem of reducing the amount of data required to represent the digital image. Compression is achieved by the removal of one or more of three basic data redundancies: (1) Coding redundancy, which is present when less than optimal (i.e. the smallest length) code words are used; (2) Interpixel redundancy, which results from correlations between the pixels of an image & (3) psycho visual redundancy which is due to data that is ignored by the human visual system (i.e. visually nonessential information). Huffman codes contain the smallest possible number of code symbols (e.g., bits) per source symbol (e.g., grey level value) subject to the constraint that the source symbols are coded one at a time. So, Huffman coding when combined with technique of reducing the image redundancies using Discrete Cosine Transform (DCT) helps in compressing the image data to a very good extent. The Discrete Cosine Transform (DCT) is an example of transform coding. The current JPEG standard uses the DCT as its basis. The DC relocates the highest energies to the upper left corner of the image. The lesser energy or information is relocated into other areas. The DCT is fast. It can be quickly calculated and is best for images with smooth edges like photos with human subjects. The DCT coefficients are all real numbers unlike the Fourier Transform. The Inverse Discrete Cosine Transform (IDCT) can be used to retrieve the image from its transform representation. The Discrete wavelet transform (DWT) has gained widespread acceptance in signal processing and image compression. Because of their inherent multi-resolution nature, wavelet-coding schemes are especially suitable for applications where scalability and tolerable degradation are important. Recently the JPEG committee has released its new image coding standard, JPEG-2000, which has been based upon DWT

    Grayscale and colour image Codec based on matching pursuit in the spatio-frequency domain

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    This report presents and evaluates a novel idea for scalable lossy colour image coding with Matching Pursuit (MP) performed in a transform domain. The benefits of the idea of MP performed in the transform domain are analysed in detail. The main contribution of this work is extending MP with wavelets to colour coding and proposing a coding method. We exploit correlations between image subbands after wavelet transformation in RGB colour space. Then, a new and simple quantisation and coding scheme of colour MP decomposition based on Run Length Encoding (RLE), inspired by the idea of coding indexes in relational databases, is applied. As a final coding step arithmetic coding is used assuming uniform distributions of MP atom parameters. The target application is compression at low and medium bit-rates. Coding performance is compared to JPEG 2000 showing the potential to outperform the latter with more sophisticated than uniform data models for arithmetic coder. The results are presented for grayscale and colour coding of 12 standard test images

    Compressed Domain Low Level Visual Descriptors

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    Content-based image retrieval and analysis have been developed for a long time, and various visual descriptors have been proposed. The need of multiple versions of an image spurs the development of image compression and descriptors based on compression domain. However, these descriptors are not able to achieve good performance in terms of quality and resolution scalability. As the appearance of JPEG 2000 compression standard, its coding algorithm and structure of bit stream make the scalability possible. The JPEG 2000 based descriptors can be developed to satisfy multiple compression levels, and keep a good performance even when the images are highly compressed. In this thesis, most existing famous and popular low level visual descriptors are reviewed. Image compression and some image analysis and retrieval approaches are introduced. Two JPEG 2000 based descriptors called state and context are proposed in this research, and an image retrieval system using these descriptors is constructed. Experiments are conducted and the results indicate the proposed descriptors have a good retrieval performance. State and context are further compared with industrial standard MPEG-7 descriptors and state-of-art SIFT method in multiple resolution and quality situations, and the proposed descriptors are proved to be more suitable in compression domain
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