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    Agfa CR图像增强MUSICA算法
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    资源介绍
    Image Processing
    in Computed Radiography
    Pieter Vuylsteke, Ph.D.
    Emile Schoeters, Ph.D.
    Agfa-Gevaert N.V.
    International Symposium on
    Computerized Tomography for Industrial Applications
    and Image Processing in Radiology
    Berlin, Germany
    March 15-17, 1999
    R&D Equipment
    2
    1. ABSTRACT 3
    2. INTRODUCTION 3
    3. CR IMAGE PROCESSING OVERVIEW 3
    4. IMAGE CONTRAST ENHANCEMENT 5
    4.A. Edge enhancement 5
    4.B. Dynamic range compression 7
    4.C. Multiscale contrast enhancement 7
    4.C.1. The multiscale representation 8
    4.C.2. Contrast equalization 10
    4.C.3. Frequency processing 12
    5. CONCLUSION 15
    6. ACKNOWLEDGMENTS 15
    7. REFERENCES 15
    3
    1. ABSTRACT
    This article starts with an overview of image processing techniques used in storage phosphor
    based Computed Radiography (CR) systems. Next it elaborates on a selection of image enhancement
    algorithms. Both the working principles and image quality issues are discussed. The main focus is on
    multiscale image enhancement, which has become state-of-the-art.
    2. INTRODUCTION
    Since the early days of CR technology developers have investigated solutions for bridging the
    gap between the very large dynamic range that characterizes the CR detector and the limited range of
    the output medium and viewing process. A considerable part of image processing functionality in
    current CR systems deals directly or indirectly with the issue of manipulating image contrast, in such
    a way that all relevant image features are rendered to an appropriate level of visibility, despite the
    restriction of viewing density range. CR equipment manufacturers have adopted basic image
    processing techniques, or they have developed dedicated solutions.
    With this article it is our aim to provide a better understanding of the essential image
    enhancement techniques of CR systems, what their purpose is, how they operate, and how they affect
    image quality.
    3. CR IMAGE PROCESSING OVERVIEW
    A simplified diagram of the image processing operations in current CR systems is depicted in
    Fig. 3.1. The ensemble of operations applied to the stream of image data could be roughly entitled
    ‘image enhancement’. The role of image processing functions within this data path is to improve the
    visual quality of the CR image in terms of spatial resolution, sharpness, contrast resolution, dynamic
    range, SNR. The processing efforts in the main path have to do with maximizing the information
    transfer to the viewer. The enhancement of image contrast is the main topic of this article and will be
    elaborated in section 4.
    The image processing operations are controlled by parameters, which often are assigned a
    value in accordance with the examination type. The predefined parameter values are stored in tables,
    with entries for each examination type. Specification of the examination type is done immediately
    before or after each exposure by means of an identification terminal, and hence is prone to human
    errors.
    In current CR systems some image processing functions are controlled by internal parameters
    which are derived from the actual image data. The parameter values are estimated by heuristic
    algorithms. This way the kind and degree of enhancement are adapted to the specific characteristics of
    the image in terms of density levels, dynamic range, noise level, or the presence of irrelevant regions
    like collimation borders. In most cases a reduced version of the original image is used as input for
    analysis, since this still contains the essential data for the task at hand. Although the final purpose of
    the analysis work is very similar among different equipment, most algorithms are proprietary, so that
    only little is published about their actual implementation.
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