Fuzzy Filters for Image Processing

This book covers a wide range of both theoretical and practical applications of fuzzy filters for image processing. The focus is on problems of noise removal, edge detection and segmentation, image enhancement and further specific applications of fuzzy filters. How soft computing techniques such as...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Nachtegael, Mike (Editor, http://id.loc.gov/vocabulary/relators/edt), van der Weken, Dietrich (Editor, http://id.loc.gov/vocabulary/relators/edt), van de Ville, Dimitri (Editor, http://id.loc.gov/vocabulary/relators/edt), Kerre, Etienne E. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003.
Edition:1st ed. 2003.
Series:Studies in Fuzziness and Soft Computing, 122
Subjects:
Online Access:Full Text via HEAL-Link
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490 1 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 122 
505 0 |a 1. Fuzzy Filters for Noise Removal -- 2. Fuzzy Filters for Noise Reduction in Images -- 3. Real-time Image Noise Cancellation Based on Fuzzy Similarity -- 4. Fuzzy Rule-Based Color Filtering Using Statistical Indices -- 5. Fuzzy Based Image Segmentation -- 6. Fuzzy Thresholding and Histogram Analysis -- 7. Color Image Segmentation by Analysis of 3D Histogram with Fuzzy Morphological Filters -- 8. Fast and Robust Fuzzy Edge Detection -- 9. Fuzzy Data Fusion for Multiple Cue Image and Video Segmentation -- 10. Fuzzy Image Enhancement in the Framework of Logarithmic Models -- 11. Observer-Dependent Image Enhancement -- 12. Fuzzy Techniques in Digital Image Processing and Shape Analysis -- 13. Adaptive Fuzzy Filters and Their Application to Online Maneuvering Target Tracking -- 14. Lossy Image Compression and Reconstruction Based on Fuzzy Relational Equation -- 15. Avoidance of Highlights through ILFOs in Automated Visual Inspection -- Appendix Color Images. 
520 |a This book covers a wide range of both theoretical and practical applications of fuzzy filters for image processing. The focus is on problems of noise removal, edge detection and segmentation, image enhancement and further specific applications of fuzzy filters. How soft computing techniques such as fuzzy set theory and fuzzy logic can be successfully applied to these problems is demonstrated. Often these techniques are complementary to existing classical techniques and contribute to a more robust performance. The book is written by international experts giving an overview of the current state of the art of fuzzy filters for image processing and can be used as a reference for researchers and practitioners in the field. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
650 0 |a Computer simulation. 
650 0 |a Optical data processing. 
650 1 4 |a Mathematical and Computational Engineering.  |0 http://scigraph.springernature.com/things/product-market-codes/T11006 
650 2 4 |a Simulation and Modeling.  |0 http://scigraph.springernature.com/things/product-market-codes/I19000 
650 2 4 |a Image Processing and Computer Vision.  |0 http://scigraph.springernature.com/things/product-market-codes/I22021 
650 2 4 |a Applications of Mathematics.  |0 http://scigraph.springernature.com/things/product-market-codes/M13003 
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700 1 |a van de Ville, Dimitri.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Kerre, Etienne E.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
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