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Registration accuracy and quality of real-life images
- Source :
- PLoS ONE, Vol 7, Iss 7, p e40558 (2012), PLoS ONE
- Publication Year :
- 2012
- Publisher :
- Public Library of Science (PLoS), 2012.
-
Abstract
- Background A common registration problem for the application of consumer device is to align all the acquired image sequences into a complete scene. Image alignment requires a registration algorithm that will compensate as much as possible for geometric variability among images. However, images captured views from a real scene usually produce different distortions. Some are derived from the optic characteristics of image sensors, and others are caused by the specific scenes and objects. Methodology/Principal Findings An image registration algorithm considering the perspective projection is proposed for the application of consumer devices in this study. It exploits a multiresolution wavelet-based method to extract significant features. An analytic differential approach is then proposed to achieve fast convergence of point matching. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based modified Levenberg-Marquardt method. Due to its feature-based and nonlinear characteristic, it converges considerably faster than most other methods. In addition, vignette compensation and color difference adjustment are also performed to further improve the quality of registration results. Conclusions/Significance The performance of the proposed method is evaluated by testing the synthetic and real images acquired by a hand-held digital still camera and in comparison with two registration techniques in terms of the squared sum of intensity differences (SSD) and correlation coefficient (CC). The results indicate that the proposed method is promising in registration accuracy and quality, which are statistically significantly better than other two approaches.
- Subjects :
- Image formation
Computer science
Image quality
Image Processing
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image registration
Top-hat transform
lcsh:Medicine
Image processing
Computer Applications
Wavelet
Engineering
Image texture
Digital image processing
Image Interpretation, Computer-Assisted
Computer vision
Image sensor
Image warping
lcsh:Science
Image resolution
Mathematical Computing
Image restoration
Feature detection (computer vision)
Multidisciplinary
business.industry
Software Tools
Binary image
Applied Mathematics
lcsh:R
Digital imaging
Software Engineering
Point set registration
Real image
Image Enhancement
Subpixel rendering
Computing Methods
Automatic image annotation
Computer Science
Signal Processing
lcsh:Q
Artificial intelligence
business
Information Technology
Algorithms
Mathematics
Homography (computer vision)
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 7
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....047adbc0ac24e6e70f5833f6885116ce