This text provides insight into the design of optimal image processing operators for implementation directly into digital hardware. Starting with simple restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications. The text is aimed principally at electronics engineers and computer scientists, but will also be of interest to anyone working with digital images

    Chapter 1. Introduction. Chapter 2. What is a logic-based filter? 2.1. Error criterion -- 2.2. Filter constraints -- 2.3. Window constraint -- 2.4. Translation invariance -- 2.5. Filter windows -- 2.6. Filter design -- 2.7. Minimizing the MAE -- 2.8. Summary -- References

    Chapter 3. How accurate is the logic-based filter? 3.1. Optimum filter error -- 3.2. Other applications -- 3.3. Summary -- References

    Chapter 4. How do you train the filter for a task? 4.1. Effect of window size -- 4.2. Training errors -- 4.3. In defense of training set approaches -- 4.4. Summary -- References

    Chapter 5. Increasing filters and mathematical morphology. 5.1. Constraints on the filter function -- 5.2. Statistical relevance -- 5.3. Summary -- References

    Chapter 6. The median filter and its variants. 6.1. The grayscale median as a special case of a generalized WOS filter -- 6.2. Binary WOS filters -- 6.3. Positive and negative medians -- 6.4. Weighted median filters -- 6.5. Optimum design of weighted rank and median filters -- 6.6. Weight-monotonic property -- 6.7. Design of weighted median filters -- 6.8. Summary -- References

    Chapter 7. Extension to grayscale. 7.1. Stack filters -- 7.2. Grayscale morphology -- 7.3. Computational morphology for beginners -- 7.4. Elemental erosion -- 7.5. Aperture filters -- 7.6. Grayscale applications -- 7.7. Summary -- References

    Chapter 8. Grayscale implementation. 8.1. Grayscale training issues -- 8.2. Hardware implementation -- 8.3. Stack filter -- 8.4. Grayscale morphology -- 8.5. Computational morphology and aperture filters -- 8.6. Efficient architecture for computational morphology and aperture filters -- 8.7. Summary -- References

    Chapter 9. Case study: noise removal from astronomical images. 9.1. CCD noise in astronomical and solar images -- 9.2. Soft morphological filters -- 9.3. Results -- 9.4. Hardware implementation -- 9.5. Summary -- References

    Chapter 10. Conclusions -- Reference


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    Title :

    Logic-based nonlinear image processing




    Publication date :

    2007


    Size :

    1 online resource (xiii, 147 p. : ill.)


    Remarks:

    Campusweiter Zugriff (Universität Hannover) - Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots.
    "SPIE digital library. - System requirements: Adobe Acrobat Reader. - Includes bibliographical references and index. - Title from PDF t.p. (viewed on 8/23/09)
    Includes bibliographical references and index
    Restricted to subscribers or individual electronic text purchasers
    System requirements: Adobe Acrobat Reader




    Type of media :

    Book


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :


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