Fast non-blind deconvolution based on 2D point spread function database for real-time ultrasound imaging

Author(s):  
Jooyoung Kang ◽  
Sung-Chan Park ◽  
Kyuhong Kim ◽  
Jung-Ho Kim
2013 ◽  
Vol 33 (4) ◽  
pp. 0428001 ◽  
Author(s):  
郭玲玲 Guo Lingling ◽  
吴泽鹏 Wu Zepeng ◽  
张立国 Zhang Liguo ◽  
任建岳 Ren Jianyue

2014 ◽  
Vol 47 (1) ◽  
pp. 17-26 ◽  
Author(s):  
David Pastor ◽  
Tomasz Stefaniuk ◽  
Piotr Wróbel ◽  
Carlos J. Zapata-Rodríguez ◽  
Rafał Kotyński

2011 ◽  
Vol 04 (04) ◽  
pp. 385-393 ◽  
Author(s):  
THOMAS JETZFELLNER ◽  
VASILIS NTZIACHRISTOS

In this paper, we consider the use of blind deconvolution for optoacoustic (photoacoustic) imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the system. The method is demonstrated with optoacoustic measurement obtained from six-day-old mice, imaged in the near-infrared using a broadband hydrophone in a circular scanning configuration. We find that estimates of the unknown point spread function, achieved by blind deconvolution, improve the resolution and contrast in the images and show promise for enhancing optoacoustic images.


2018 ◽  
Vol 29 (1) ◽  
pp. 189 ◽  
Author(s):  
Ghada Sabah Karam

Blurring image caused by a number of factors such as de focus, motion, and limited sensor resolution. Most of existing blind deconvolution research concentrates at recovering a single blurring kernel for the entire image. We proposed adaptive blind- non reference image quality assessment method for estimation the blur function (i.e. point spread function PSF) from the image acquired under low-lighting conditions and defocus images using Bayesian Blind Deconvolution. It is based on predicting a sharp version of a blurry inter image and uses the two images to solve a PSF. The estimation down by trial and error experimentation, until an acceptable restored image quality is obtained. Assessments the qualities of images have done through the applications of a set of quality metrics. Our method is fast and produces accurate results.


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