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Depth from Defocus Based on Geometric Constraints      Journal of Computers


Accession number:  14182785

  Title:  Depth from defocus based on geometric constraints
  Authors:  Qiufeng Wu1; Kuanquan Wang1 ; Wangmeng Zuo1  
  Author affiliation:  1 Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China  
  Source title:  Journal of Computers
  Abbreviated source title:  J. Comput. (Finland)
  Volume:  9
  Issue:  1
  Publication date:  Jan. 2014
  Pages:  44-51
  Language:  English
  ISSN:  1796-203X  
  Document type:  Journal article (JA)
  Publisher:  Academy Publisher
  Country of publication:  Finland
  Material Identity Number:  DW39-2014-005  
  Abstract:  This paper proposes a Depth from Defocus (DFD) model based on geometric constraints. The two measured defocused images match with each other with this method including geometric constraints, which bypasses estimation of the radiance. These geometric constraints vary with different relative position of image plane and image focus. The experimental results on the synthetic and real images show that this method is accurate and efficient. The experimental results on the synthetic images with noise show that this method is robust to the images with Salt &Pepper and Poisson noise.
  Number of references:  20
  Inspec controlled terms:  geometry  -  image matching  -  stochastic processes  
  Uncontrolled terms:  depth from defocus  -  geometric constraints  -  DFD model  -  defocused image matching  -  radiance estimation  -  image plane position  -  image focus  -  synthetic images  -  real images  -  Salt &Pepper noise  -  Poisson noise  
  Inspec classification codes:  B6135E Image recognition -  B0250 Combinatorial mathematics -  B0240Z Other topics in statistics -  C5260B Computer vision and image processing techniques -  C1160 Combinatorial mathematics -  C1140Z Other topics in statistics
  Treatment:  Practical (PRA); Theoretical or Mathematical (THR)  
  Discipline:  Electrical/Electronic engineering (B); Computers/Control engineering (C)
  DOI:  10.4304/jcp.9.1.44-51
  IPC Code:  G06T  SECTION G PHYSICS
COMPUTING; CALCULATING; COUNTING score computers for games , , ; combinations of writing implements with computing devices
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL specially adapted for particular applications, see the relevant subclasses, e.g. , , 6

        
  Database:  Inspec
   Copyright 2014, The Institution of Engineering and Technology

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wuqiufeng_2008: ½ð±Ò+10, ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸, ллÄúÁË 2014-09-13 20:41:58
oven1986: LS-EPI+1, ¸ÐлӦÖú£¡ 2014-09-14 01:14:21
Accession number:  14182785

  Title:  Depth from defocus based on geometric constraints
  Authors:  Qiufeng Wu1; Kuanquan Wang1 ; Wangmeng Zuo1  
  Author affiliation:  1 Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China  
  Source title:  Journal of Computers
  Abbreviated source title:  J. Comput. (Finland)
  Volume:  9
  Issue:  1
  Publication date:  Jan. 2014
  Pages:  44-51
  Language:  English
  ISSN:  1796-203X  
  Document type:  Journal article (JA)
  Publisher:  Academy Publisher
  Country of publication:  Finland
  Material Identity Number:  DW39-2014-005  
  Abstract:  This paper proposes a Depth from Defocus (DFD) model based on geometric constraints. The two measured defocused images match with each other with this method including geometric constraints, which bypasses estimation of the radiance. These geometric constraints vary with different relative position of image plane and image focus. The experimental results on the synthetic and real images show that this method is accurate and efficient. The experimental results on the synthetic images with noise show that this method is robust to the images with Salt &Pepper and Poisson noise.
  Number of references:  20
  Inspec controlled terms:  geometry  -  image matching  -  stochastic processes  
  Uncontrolled terms:  depth from defocus  -  geometric constraints  -  DFD model  -  defocused image matching  -  radiance estimation  -  image plane position  -  image focus  -  synthetic images  -  real images  -  Salt &Pepper noise  -  Poisson noise  
  Inspec classification codes:  B6135E Image recognition -  B0250 Combinatorial mathematics -  B0240Z Other topics in statistics -  C5260B Computer vision and image processing techniques -  C1160 Combinatorial mathematics -  C1140Z Other topics in statistics
  Treatment:  Practical (PRA); Theoretical or Mathematical (THR)  
  Discipline:  Electrical/Electronic engineering (B); Computers/Control engineering (C)
  DOI:  10.4304/jcp.9.1.44-51
  IPC Code:  G06T  •SECTION G PHYSICS
•COMPUTING; CALCULATING; COUNTING score computers for games , , ; combinations of writing implements with computing devices
•IMAGE DATA PROCESSING OR GENERATION, IN GENERAL specially adapted for particular applications, see the relevant subclasses, e.g. , , 6

        
  Database:  Inspec
   Copyright 2014, The Institution of Engineering and Technology


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wuqiufeng_2008

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