A portable system for high-resolution digital image acquisition using wavelet image compression

Author(s):  
U. Schelinski ◽  
S. Danz ◽  
K. Frommhagen ◽  
M. Scholles ◽  
M. Schwarzenberg
2006 ◽  
Vol 14 (6) ◽  
pp. 44-47
Author(s):  
Radhika Subramanian

Imagine what a researcher 50 years ago would think of the technology available in today's modern research labs, where the ability to photograph and videotape live cell images in high resolution has spurred numerous advances in the sciences. Additionally, technology's shift from analog to digital image acquisition has enhanced scientific collaboration and analysis abilities, perhaps in ways our predecessors could never have imagined. However, the massive quantities of data that result from these image acquisition techniques, and subsequent storage requirements, have created unforeseen challenges. While we describe life science applications, the methods described in this article are equally applicable in physical sciences laboratories.


Author(s):  
Vinod K. Berry ◽  
Xiao Zhang

In recent years it became apparent that we needed to improve productivity and efficiency in the Microscopy Laboratories in GE Plastics. It was realized that digital image acquisition, archiving, processing, analysis, and transmission over a network would be the best way to achieve this goal. Also, the capabilities of quantitative image analysis, image transmission etc. available with this approach would help us to increase our efficiency. Although the advantages of digital image acquisition, processing, archiving, etc. have been described and are being practiced in many SEM, laboratories, they have not been generally applied in microscopy laboratories (TEM, Optical, SEM and others) and impact on increased productivity has not been yet exploited as well.In order to attain our objective we have acquired a SEMICAPS imaging workstation for each of the GE Plastic sites in the United States. We have integrated the workstation with the microscopes and their peripherals as shown in Figure 1.


Author(s):  
John Mansfield

Advances in camera technology and digital instrument control have meant that in modern microscopy, the image that was, in the past, typically recorded on a piece of film is now recorded directly into a computer. The transfer of the analog image seen in the microscope to the digitized picture in the computer does not mean, however, that the problems associated with recording images, analyzing them, and preparing them for publication, have all miraculously been solved. The steps involved in the recording an image to film remain largely intact in the digital world. The image is recorded, prepared for measurement in some way, analyzed, and then prepared for presentation.Digital image acquisition schemes are largely the realm of the microscope manufacturers, however, there are also a multitude of “homemade” acquisition systems in microscope laboratories around the world. It is not the mission of this tutorial to deal with the various acquisition systems, but rather to introduce the novice user to rudimentary image processing and measurement.


1999 ◽  
Author(s):  
Charles L. Smith ◽  
Wei-Kom Chu ◽  
Randy Wobig ◽  
Hong-Yang Chao ◽  
Charles Enke

Author(s):  
R. S. Hansen ◽  
D. W. Waldram ◽  
T. Q. Thai ◽  
R. B. Berke

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.


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