Title :
Wiener based spatial resolution enhancement of MRI sequences of the vocal tract: A comparison between two correlation models
Author :
Martins, A.L.D. ; Mascarenhas, Nelson D. A.
Author_Institution :
Dept. de Comput., Univ. Fed. de Sao Carlos, Sao Carlos, Brazil
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
Articulatory Synthesis consists in reproducing speech based on models of the vocal tract and of articulatory processes. Recent advances in MRI allowed for important improvements with respect to the speech comprehension. However, one of the main challenges is the high-quality acquisition of images. Since adopting more powerful acquisition devices might be financially inviable, a more feasible solution is to perform the resolution enhancement using only image processing techniques. In a previous work, we proposed a Wiener based super resolution technique for the spatial resolution enhancement. A separable Markovian model was used in the characterization of the spatial correlation structures. In this paper we report on a study that compares this model with an isotropic model. According to the conducted experiments, the isotropic model outperformed the separable Markovian model in all cases. Moreover, the adopted super resolution method out-performed the two available approaches used in this context.
Keywords :
Wiener filters; biomedical MRI; filtering theory; image enhancement; image reconstruction; image resolution; image sequences; maximum likelihood estimation; medical image processing; speech processing; speech synthesis; MRI sequences; Wiener based spatial resolution enhancement; articulatory processes; articulatory synthesis; image processing techniques; isotropic model; maximum a posteriori probability estimation; speech comprehension; speech reproduction; super resolution image reconstruction method; vocal tract; Computational modeling; Correlation; Magnetic resonance imaging; Numerical models; Spatial resolution; Speech; Articulatory synthesis; magnetic resonance imaging; spatial resolution enhancement; super resolution image reconstruction;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6466998