Logic-based nonlinear image processing

Logic-based nonlinear image processing

by Marshall, Stephen

Type Book
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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.

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Title Statements

  • Full title :Logic-based nonlinear image processing / Stephen Marshall.

Summary

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.

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Edition Statements

  • Publication Date:©2007.

Publication Statements

  • Publisher(s):SPIE
  • Place of Publication:Bellingham, Wash
  • Language:eng
  • Publication Date:©2007.

Notes

"SPIE digital library."

Title from PDF title page (viewed 8/23/09).

The Physical Object

  • Description:1 online resource (xiii, 147 pages) : : illustrations

Edition Identifiers

  • ISBN:9780819479006, 0819479004
  • DOI:10.1117/3.677549
  • oclc:ocn435971844
  • LC Classification:TA1637
  • Dewey Decimal:621.36/7

Table of Contents

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. Gr…

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Subjects

Digital filters (Mathematics) digital imaging Filtres numériques (Mathématiques) Image processing -- Digital techniques Nonlinear theories TECHNOLOGY & ENGINEERING -- Mechanical Théories non linéaires Traitement d'images -- Techniques numér…

Writers

Marshall, Stephen

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