Theoretical performance assessment and empirical analysis of super-resolution under unknown affine sensor motion
| Autor: | John R. Valenzuela, Joel W LeBlanc, Brian J. Thelen |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Perspective (graphical) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing 02 engineering and technology Iterative reconstruction Inverse problem Translation (geometry) 01 natural sciences Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials 010309 optics Reduction (complexity) Optics Motion estimation 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Affine transformation business Algorithm |
| Zdroj: | Journal of the Optical Society of America. A, Optics, image science, and vision. 33(4) |
| ISSN: | 1520-8532 |
| Popis: | This paper deals with super-resolution (SR) processing and associated theoretical performance assessment for under-sampled video data collected from a moving imaging platform with unknown motion and assuming a relatively flat scene. This general scenario requires joint estimation of the high-resolution image and the parameters that determine a projective transform that relates the collected frames to one another. A quantitative assessment of the variance in the random error as achieved through a joint-estimation approach (e.g., SR image reconstruction and motion estimation) is carried out via the general framework of M-estimators and asymptotic statistics. This approach provides a performance measure on estimating the fine-resolution scene when there is a lack of perspective information and represents a significant advancement over previous work that considered only the more specific scenario of mis-registration. A succinct overview of the theoretical framework is presented along with some specific results on the approximate random error for the case of unknown translation and affine motions. A comparison is given between the approximated random error and that actually achieved by an M-estimator approach to the joint-estimation problem. These results provide insight on the reduction in SR reconstruction accuracy when jointly estimating unknown inter-frame affine motion. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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