20 research outputs found

    Error resilience analysis of wireless image transmission using JPEG, JPEG 2000 and JPWL

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    The wireless extension of the JPEG 2000 standard formally known as JPWL is the newest international standard for still image compression. Different from all previous standards, this new standard was created specifically for wireless imaging applications. This paper examines the error resilience performance of the JPEG, JPEG 2000 and JPWL standards in combating multi-path and fading impairments in Rayleigh fading channels. Comprehensive objective and subjective results are presented in relation to the error resilience performance of these three standards under various conditions. The major findings in this paper reveal that a CRC approach is not a viable option for protecting wireless image data when not used in conjunction with an efficient retransmission strategy. In addition, the Reed-Solomon error correction codes in JPWL provide strong protection for wireless image transmission. However, any stronger protection beyond RS(64,32) yields diminishing returns

    JPWL - an Extension of JPEG 2000 for Wireless Imaging

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    In this paper, we present an overview of the JPWL standardization activity. JPWL is an extension of JPEG 2000 for the efficient transmission of JPEG 2000 images over an error-prone wireless network. More specifically, JPWL supports a set of tools for error protection and correction, including Forward Error Correcting codes (FEC), Unequal Error Protection (UEP), data partitioning and interleaving

    JPWL: JPEG 2000 for Wireless Applications

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    In this paper, we present the current status of the JPWL standardization work item. JPWL is an extension of the JPEG 2000 baseline specification in order to enable the efficient transmission of JPEG 2000 codestream over an error-prone network. In particular, JPWL supports a set of tools and methods for error protection and correction such as Forward Error Correcting (FEC) codes, Unequal Error Protection (UEP), and data partitioning and interleaving. We then evaluate the performance of the JPWL Error Protection Block (EPB) tool. We consider two configurations of EPB: to protect the Main and Tile-part headers, or to protect the whole codestream using UEP. Experimental results show a significant quality improvement when using EPB compared to baseline JPEG 2000

    LAR Image transmission over fading channels: a hierarchical protection solution

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    International audienceThe aim of this paper is to present an efficient scheme to transmit a compressed digital image over a non frequency selective Rayleigh fading channel. The proposed scheme is based on the Locally Adaptive Resolution (LAR) algorithm, and the Reed-Solomon error correcting code is used to protect the data against the channel errors. In order to optimize the protection rate and ensure better protection we introduce an Unequal Error Protection (UEP) strategy, where we take the hierarchy of the information into account. The digital communication system also includes appropriate interleaving and differential modulation. Simulation results clearly show that our scheme presents an efficient solution for image transmission over wireless channels, and provides a high quality of service, outperforming the JPWL scheme in high bit error rate conditions

    Locally Adaptive Resolution (LAR) codec

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    The JPEG committee has initiated a study of potential technologies dedicated to future generation image compression systems. The idea is to design a new norm of image compression, named JPEG AIC (Advanced Image Coding), together with advanced evaluation methodologies, closely matching to human vision system characteristics. JPEG AIC thus aimed at defining a complete coding system able to address advanced functionalities such as lossy to lossless compression, scalability (spatial, temporal, depth, quality, complexity, component, granularity...), robustness, embed-ability, content description for image handling at object level... The chosen compression method would have to fit perceptual metrics defined by the JPEG community within the JPEG AIC project. In this context, we propose the Locally Adaptive Resolution (LAR) codec as a contribution to the relative call for technologies, tending to fit all of previous functionalities. This method is a coding solution that simultaneously proposes a relevant representation of the image. This property is exploited through various complementary coding schemes in order to design a highly scalable encoder. The LAR method has been initially introduced for lossy image coding. This efficient image compression solution relies on a content-based system driven by a specific quadtree representation, based on the assumption that an image can be represented as layers of basic information and local texture. Multiresolution versions of this codec have shown their efficiency, from low bit rates up to lossless compressed images. An original hierarchical self-extracting region representation has also been elaborated: a segmentation process is realized at both coder and decoder, leading to a free segmentation map. This later can be further exploited for color region encoding, image handling at region level. Moreover, the inherent structure of the LAR codec can be used for advanced functionalities such as content securization purposes. In particular, dedicated Unequal Error Protection systems have been produced and tested for transmission over the Internet or wireless channels. Hierarchical selective encryption techniques have been adapted to our coding scheme. Data hiding system based on the LAR multiresolution description allows efficient content protection. Thanks to the modularity of our coding scheme, complexity can be adjusted to address various embedded systems. For example, basic version of the LAR coder has been implemented onto FPGA platform while respecting real-time constraints. Pyramidal LAR solution and hierarchical segmentation process have also been prototyped on DSPs heterogeneous architectures. This chapter first introduces JPEG AIC scope and details associated requirements. Then we develop the technical features, of the LAR system, and show the originality of the proposed scheme, both in terms of functionalities and services. In particular, we show that the LAR coder remains efficient for natural images, medical images, and art images

    Privacy Enabling Technology for Video Surveillance

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    In this paper, we address the problem privacy in video surveillance. We propose an efficient solution based on transform-domain scrambling of regions of interest in a video sequence. More specifically, the sign of selected transform coefficients is flipped during encoding. We address more specifically the case of Motion JPEG 2000. Simulation results show that the technique can be successfully applied to conceal information in regions of interest in the scene while providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of distortion introduced. This is achieved with a small impact on coding performance and negligible computational complexity increase. In the proposed video surveillance system, heterogeneous clients can remotely access the system through the Internet or 2G/3G mobile phone network. Thanks to the inherently scalable Motion JPEG 2000 codestream, the server is able to adapt the resolution and bandwidth of the delivered video depending on the usage environment of the client

    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

    Utilização da Norma JPEG2000 para codificar proteger e comercializar Produtos de Observação Terrestre

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    Applications like, change detection, global monitoring, disaster detection and management have emerging requirements that need the availability of large amounts of data. This data is currently being capture by a multiplicity of instruments and EO (Earth Observation) sensors originating large volumes of data that needs to be stored, processed and accessed in order to be useful – as an example, ENVISAT accumulates, in a yearly basis, several hundred terabytes of data. This need to recover, store, process and access brings some interesting challenges, like storage space, processing power, bandwidth and security, just to mention a few. These challenges are still very important on today’s technological world. If we take a look for example at the number of subscribers of ISP (Internet Service Providers) broadband services on the developed world today, one can notice that broadband services are still far from being common and dominant. On the underdeveloped countries the picture is even dimmer, not only from a bandwidth point of view but also in all other aspects regarding information and communication technologies (ICTs). All this challenges need to be taken into account if a service is to reach the broadest audience possible. Obviously protection and securing of services and contents is an extra asset that helps on the preservation of possible business values, especially if we consider such a costly business as the space industry. This thesis presents and describes a system which allows, not only the encoding and decoding of several EO products into a JPEG2000 format, but also supports some of the security requirements identified previously that allows ESA (European Space Agency) and related EO services to define and apply efficient EO data access security policies and even to exploit new ways to commerce EO products over the Internet.Aplicações como, detecção de mudanças no terreno, monitorização planetária, detecção e gestão de desastres, têm necessidades prementes que necessitam de vastas quantidades de dados. Estes dados estão presentemente a ser capturados por uma multiplicidade de instrumentos e sensores de observação terrestre, que originam uma enormidade de dados que necessitam de ser armazenados processados e acedidos de forma a se tornarem úteis – por exemplo, a ENVISAT acumula anualmente varias centenas de terabytes de dados. Esta necessidade de recuperar, armazenar, processar e aceder introduz alguns desafios interessantes como o espaço de armazenamento, poder de processamento, largura de banda e segurança dos dados só para mencionar alguns. Estes desafios são muito importantes no mundo tecnológico de hoje. Se olharmos, por exemplo, ao número actual de subscritores de ISP (Internet Service Providers) de banda larga nos países desenvolvidos podemos ficar surpreendidos com o facto do número de subscritores desses serviços ainda não ser uma maioria da população ou dos agregados familiares. Nos países subdesenvolvidos o quadro é ainda mais negro não só do ponto de vista da largura de banda mas também de todos os outros aspectos relacionados com Tecnologias da Informação e Comunicação (TICs). Todos estes aspectos devem ser levados em consideração se se pretende que um serviço se torne o mais abrangente possível em termos de audiências. Obviamente a protecção e segurança dos conteúdos é um factor extra que ajuda a preservar possíveis valores de negócio, especialmente considerando industrias tão onerosas como a Industria Espacial. Esta tese apresenta e descreve um sistema que permite, não só a codificação e descodificação de diversos produtos de observação terrestre para formato JPEG2000 mas também o suporte de alguns requisitos de segurança identificados previamente que permitem, á Agência Espacial Europeia e a outros serviços relacionados com observação terrestre, a aplicação de politicas eficientes de acesso seguro a produtos de observação terrestre, permitindo até o aparecimento de novas forma de comercialização de produtos de observação terrestre através da Internet

    Processing and codification images based on jpg standard

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    This project raises the necessity to use the image compression currently, and the different methods of compression and codification. Specifically, it will deepen the lossy compression standards with the JPEG [1] standard. The main goal of this project is to implement a Matlab program, which encode and compress an image of any format in a “jpg” format image, through JPEG standard premises. JPEG compresses images based on their spatial frequency, or level of detail in the image. Areas with low levels of detail, like blue sky, are compressed better than areas with high levels of detail, like hair, blades of trees, or hard-edged transitions. The JPEG algorithm takes advantage of the human eye's increased sensitivity to small differences in brightness versus small differences in color, especially at higher frequencies. The JPEG algorithm first transforms the image from RGB to the luminance/chrominance (Y-Cb-Cr) color space, or brightness/grayscale (Y) from the two color components. The algorithm then downsamples the color components and leaves the brightness component alone. Next, the JPEG algorithm approximates 8x8 blocks of pixels with a base value representing the average, plus some frequency coefficients for nearby variations. Quantization, then downsamples these DCT coefficients. Higher frequencies and chroma are quantized by larger coefficients than lower frequencies and luminance. Thus more of the brightness information is kept than the higher frequencies and color values. So the lower the level of detail and the fewer abrupt color or tonal transitions, the more efficient the JPEG algorithm becomes. ____________________________________________________________________________________________________________________________En este proyecto se aborda la necesidad de comprimir las imágenes en la actualidad, además de explicar los diferentes métodos posibles para la compresión y codificación de imágenes. En concreto, se va a profundizar en los estándares de compresión con pérdidas, mediante el estándar JPEG. El pilar central del proyecto será la realización de un programa en Matlab que codifique y comprima una imagen de cualquier formato en una imagen con formato “jpg”, mediante las premisas del estándar JPEG. La compresión de imágenes con JPEG está basada en la frecuencia espacial, o nivel de detalle, de las imágenes. Las áreas con bajo nivel de detalle, es decir, homogéneas, se pueden comprimir mejor que áreas con gran nivel de detalle o las transiciones de los bordes. El algoritmo JPEG se aprovecha de la sensibilidad del ojo humano a pequeñas diferencias de brillo frente a las de color, especialmente con altas frecuencias. El algoritmo JPEG primero transforma la paleta de colores de la imagen RGB a un espacio de color de luminancia/crominancia (Y-Cb-Cr), o brillo/escala de grises (Y) con las dos componentes del color. El algoritmo a continuación disminuye las componentes del color y deja solo la componente del brillo. A continuación, se aproxima la imagen en bloques de 8x8 pixeles con un valor base promedio, además de coeficientes de frecuencia de variaciones cercanas. Con la cuantificación, se disminuyen la resolución de los coeficientes de la DCT. Las frecuencias más altas y crominancias se cuantifican con los coeficientes de bajas frecuencias y luminancia. De esta forma, se mantienen mayor información de brillo que de altas frecuencias y colores. Por lo tanto, cuanto más homogénea sea la imagen (menor nivel de detalle y menos transiciones tonales abruptas) más eficiente será el algoritmo JPEG.Ingeniería Técnica en Sistemas de Telecomunicació
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