[Adaptive super resolution algorithm for under-sampled images].
Nan Fang Yi Ke Da Xue Xue Bao
; 29(4): 656-8, 2009 Apr.
Article
en Zh
| MEDLINE
| ID: mdl-19403388
OBJECTIVE: A new algorithm of adaptive super-resolution (SR) reconstruction based on the regularization parameter is proposed to reconstruct a high-resolution (HR) image from the low-resolution (LR) image sequence, which takes into full account the inaccurate estimates of motion error, point spread function (PSF) and the additive Gaussian noise in the LR image sequence. We established a novel nonlinear adaptive regularization function and analyzed experimentally its convexity to obtain the adaptive step size. This novel algorithm can effectively improve the spatial resolution of the image and the rate of convergence, which is verified by the experiment on optical images.
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Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Procesamiento de Imagen Asistido por Computador
Tipo de estudio:
Prognostic_studies
Idioma:
Zh
Revista:
Nan Fang Yi Ke Da Xue Xue Bao
Año:
2009
Tipo del documento:
Article
País de afiliación:
China