Optical Resolution Measurement
Optical Resolution Measurement - Related Videos
08:31
Three-dimensional Optical-resolution Photoacoustic Microscopy
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Cited by 27 •
2011
Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging technology capable of imaging optical absorption contrasts in vivo with cellular resolution and sensitivity. Here, we provide a visualized instruction on the experimental protocols of OR-PAM, including system configuration, system alignment, typical in vivo experimental procedures, and functional imaging schemes.
13:49
High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging
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Cited by 84 •
2011
In many biological and clinical situations it is advantageous to study cellular processes as they evolve in their native microenvironment. Here we describe the assembly and use of a low-cost fiber-optic microscope which can provide real time imaging in cell culture, animal studies, and clinical patient studies.
11:07
High-resolution Optical Mapping of the Mouse Sino-atrial Node
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Cited by 17 •
2016
Here, we present a protocol for optical mapping of electrical activity from the mouse right atrium and especially the sino-atrial node, at a high spatial and temporal resolution.
09:48
Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping
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Cited by 8 •
2016
We demonstrate use of a fiber optic distributed sensor for mapping the temperature field of mixing air jets. The Rayleigh scattering-based sensor generates thousands of data points along a single fiber to provide exceptional spatial resolution that is unattainable with traditional sensors such as thermocouples.
14:09
Quantitative Optical Microscopy: Measurement of Cellular Biophysical Features with a Standard Optical Microscope
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Cited by 11 •
2014
We describe the use of a standard optical microscope to perform quantitative measurements of cellular mass, volume, and density through a combination of bright field and differential interference contrast imagery.
FAQs
The Rayleigh limit links the smallest distinguishable separation to wavelength and aperture, while aberrations can alter the achieved performance. Resolution therefore depends on the optical conditions and imperfections of the system, not on a single nominal specification. Applying this criterion helps determine whether two nearby features should appear separately and supports comparisons among optical designs.
A point-spread function, or PSF, describes how an imaging system represents a point source, making it useful for examining resolving behavior. Its measured form provides information beyond a simple visual judgment of image quality. Changes associated with defocus or optical imperfections can expose performance losses and help explain why fine features become harder to distinguish.
Calibrated test patterns present known fine features, so the measurement can focus on the smallest feature spacing that remains distinguishable. Point sources instead support analysis through the point-spread function. Using either reference makes the assessment quantitative rather than purely descriptive, while the selected target can emphasize feature separation or the imaging system’s response.
Begin with a calibrated test pattern or point source, acquire the image, and evaluate either the smallest resolvable separation or the point-spread function. The result can then be interpreted with a criterion such as the Rayleigh limit. This workflow produces a performance value that can be compared across lenses, microscopes, telescopes, or detectors.
Resolution data can distinguish a general loss of fine-detail performance from effects associated with defocus or optical imperfections. Examining the measured separation limit or point-spread function provides a way to connect observed image degradation with the system’s optical behavior. That diagnosis supports targeted optimization rather than treating every poor image as an interchangeable quality problem.
It is useful when researchers need to compare imaging components, assess whether an instrument can separate features of interest, or interpret observations quantitatively. Applications include evaluating lenses, microscopes, telescopes, and detectors, as well as optimizing optical-system design. Reliable resolution values support quantitative imaging and more accurate interpretation of experimental observations.