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Logic-based nonlinear image processing

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Logic-based nonlinear image processing/ Stephen Marshall.
Author:	Marshall, Stephen,
Published:	Bellingham, Wash. (1000 20th St. Bellingham WA 98225-6705 USA) :SPIE, : c2007.,
Description:	1 online resource (xiii, 147 p. : ill.) :digital file. :
Notes:	"SPIE digital library."
Subject:	Image processing - Digital techniques. -
Online resource:	http://dx.doi.org/10.1117/3.677549
Online resource:	http://www.loc.gov/catdir/toc/ecip0613/2006014512.html
ISBN:	9780819479006 (electronic)

Logic-based nonlinear image processing
Marshall, Stephen,1958-

Logic-based nonlinear image processing[electronic resource] /Stephen Marshall. - Bellingham, Wash. (1000 20th St. Bellingham WA 98225-6705 USA) :SPIE,c2007. - 1 online resource (xiii, 147 p. : ill.) :digital file. - Tutorial texts in optical engineering ;v. TT72. - SPIE tutorial texts ;TT06..

"SPIE digital library."

Includes bibliographical references and index.

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.

Restricted to subscribers or individual electronic text purchasers.

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.

Mode of access: World Wide Web.

ISBN: 9780819479006 (electronic)

Standard No.: 10.1117/3.677549doiSubjects--Topical Terms:

555959
Image processing
--Digital techniques.

LC Class. No.: TA1637 / .M338 2007e

Dewey Class. No.: 621.36/7

Logic-based nonlinear image processing
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020 $a 9780819479006 (electronic)
020 $z 0819463434 (print)
020 $z 9780819463432 (print)
024 7 $a 10.1117/3.677549 $2 doi
035 $a (OCoLC)435971844
035 $a (CaBNVSL)gtp00535584
035 $a 9780819479006
040 $a CaBNVSL $c CaBNVSL $d CaBNVSL
050 4 $a TA1637 $b .M338 2007e
082 0 4 $a 621.36/7 $2 22
100 1 $a Marshall, Stephen, $d 1958- $3 877278
245 1 0 $a Logic-based nonlinear image processing $h [electronic resource] / $c Stephen Marshall.
260 $a Bellingham, Wash. (1000 20th St. Bellingham WA 98225-6705 USA) : $b SPIE, $c c2007.
300 $a 1 online resource (xiii, 147 p. : ill.) : $b digital file.
490 1 $a Tutorial texts in optical engineering ; $v v. TT72
500 $a "SPIE digital library."
500 $a System requirements: Adobe Acrobat Reader.
504 $a Includes bibliographical references and index.
505 0 $a 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.
505 0 $a Chapter 3. How accurate is the logic-based filter? 3.1. Optimum filter error -- 3.2. Other applications -- 3.3. Summary -- References.
505 0 $a 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.
505 0 $a Chapter 5. Increasing filters and mathematical morphology. 5.1. Constraints on the filter function -- 5.2. Statistical relevance -- 5.3. Summary -- References.
505 0 $a 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.
505 0 $a 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.
505 0 $a 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.
505 0 $a 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.
505 0 $a Chapter 10. Conclusions -- Reference.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a 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.
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Title from PDF t.p. (viewed on 8/23/09).
650 0 $a Image processing $x Digital techniques. $3 555959
650 0 $a Nonlinear theories. $3 527937
650 0 $a Digital filters (Mathematics) $3 596752
710 2 $a Society of Photo-optical Instrumentation Engineers. $3 700253
830 0 $a SPIE tutorial texts ; $v TT06. $3 877241
856 4 0 $u http://dx.doi.org/10.1117/3.677549
856 4 1 $3 Table of contents only $u http://www.loc.gov/catdir/toc/ecip0613/2006014512.html