Bounds for the Condition Numbers of Spatially-variant Convolution Matrices in Image Restoration Problems

Author(s):  
Stanley H. Chan ◽  
Ankit K. Jain ◽  
Truong Q. Nguyen ◽  
Edmund Y. Lam
2001 ◽  
Author(s):  
Andrew Shearer ◽  
Gerard Gorman ◽  
Triona O'Doherty ◽  
Wilhelm J. van der Putten ◽  
Peter McCarthy ◽  
...  

2018 ◽  
Vol 13 (1) ◽  
pp. 155-162 ◽  
Author(s):  
Junting Cheng ◽  
Yi Gao ◽  
Boyang Guo ◽  
Wangmeng Zuo

Author(s):  
W.A. Carrington ◽  
F.S. Fay ◽  
K.E. Fogarty ◽  
L. Lifshitz

Advances in digital imaging microscopy and in the synthesis of fluorescent dyes allow the determination of 3D distribution of specific proteins, ions, GNA or DNA in single living cells. Effective use of this technology requires a combination of optical and computer hardware and software for image restoration, feature extraction and computer graphics.The digital imaging microscope consists of a conventional epifluorescence microscope with computer controlled focus, excitation and emission wavelength and duration of excitation. Images are recorded with a cooled (-80°C) CCD. 3D images are obtained as a series of optical sections at .25 - .5 μm intervals.A conventional microscope has substantial blurring along its optical axis. Out of focus contributions to a single optical section cause low contrast and flare; details are poorly resolved along the optical axis. We have developed new computer algorithms for reversing these distortions. These image restoration techniques and scanning confocal microscopes yield significantly better images; the results from the two are comparable.


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