78 research outputs found

    WG1N5315 - Response to Call for AIC evaluation methodologies and compression technologies for medical images: LAR Codec

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    This document presents the LAR image codec as a response to Call for AIC evaluation methodologies and compression technologies for medical images.This document describes the IETR response to the specific call for contributions of medical imaging technologies to be considered for AIC. The philosophy behind our coder is not to outperform JPEG2000 in compression; our goal is to propose an open source, royalty free, alternative image coder with integrated services. While keeping the compression performances in the same range as JPEG2000 but with lower complexity, our coder also provides services such as scalability, cryptography, data hiding, lossy to lossless compression, region of interest, free region representation and coding

    Preserving data integrity of encoded medical images: the LAR compression framework

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    International audienceThrough the development of medical imaging systems and their integration into a complete information system, the need for advanced joint coding and network services becomes predominant. PACS (Picture Archiving and Communication System) aims to acquire, store and compress, retrieve, present and distribute medical images. These systems have to be accessible via the Internet or wireless channels. Thus protection processes against transmission errors have to be added to get a powerful joint source-channel coding tool. Moreover, these sensitive data require confidentiality and privacy for both archiving and transmission purposes, leading to use cryptography and data embedding solutions. This chapter introduces data integrity protection and developed dedicated tools of content protection and secure bitstream transmission for medical encoded image purposes. In particular, the LAR image coding method is defined together with advanced securization services

    An approach to summarize video data in compressed domain

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    Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2007Includes bibliographical references (leaves: 54-56)Text in English; Abstract: Turkish and Englishx, 59 leavesThe requirements to represent digital video and images efficiently and feasibly have collected great efforts on research, development and standardization over past 20 years. These efforts targeted a vast area of applications such as video on demand, digital TV/HDTV broadcasting, multimedia video databases, surveillance applications etc. Moreover, the applications demand more efficient collections of algorithms to enable lower bit rate levels, with acceptable quality depending on application requirements. In our time, most of the video content either stored, transmitted is in compressed form. The increase in the amount of video data that is being shared attracted interest of researchers on the interrelated problems of video summarization, indexing and abstraction. In this study, the scene cut detection in emerging ISO/ITU H264/AVC coded bit stream is realized by extracting spatio-temporal prediction information directly in the compressed domain. The syntax and semantics, parsing and decoding processes of ISO/ITU H264/AVC bit-stream is analyzed to detect scene information. Various video test data is constructed using Joint Video Team.s test model JM encoder, and implementations are made on JM decoder. The output of the study is the scene information to address video summarization, skimming, indexing applications that use the new generation ISO/ITU H264/AVC video

    Platforms for handling and development of audiovisual data

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    Estágio realizado na MOG Solutions e orientado por Vítor TeixeiraTese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 200

    Implementation of Image Compression Algorithm using Verilog with Area, Power and Timing Constraints

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    Image compression is the application of Data compression on digital images. A fundamental shift in the image compression approach came after the Discrete Wavelet Transform (DWT) became popular. To overcome the inefficiencies in the JPEG standard and serve emerging areas of mobile and Internet communications, the new JPEG2000 standard has been developed based on the principles of DWT. An image compression algorithm was comprehended using Matlab code, and modified to perform better when implemented in hardware description language. Using Verilog HDL, the encoder for the image compression employing DWT was implemented. Detailed analysis for power, timing and area was done for Booth multiplier which forms the major building block in implementing DWT. The encoding technique exploits the zero tree structure present in the bitplanes to compress the transform coefficients

    Combined Industry, Space and Earth Science Data Compression Workshop

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    The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

    Format-independent media resource adaptation and delivery

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