Interactive Java Tutorial
Spatial resolution is a term that refers to the number of pixels utilized in construction of a digital image. Images having higher spatial resolution are composed with a greater number of pixels than those of lower spatial resolution. This interactive tutorial explores variations in digital image spatial resolution, and how these values affect the final appearance of the image.
The tutorial initializes with a randomly selected specimen image, captured in the MIC-D digital microscope, appearing in the left-hand window entitled Specimen Image. Each specimen name includes, in parentheses, an abbreviation designating the contrast mechanism employed in obtaining the image. The following nomenclature is used: (BF), brightfield; (DF), darkfield; (OB), oblique illumination; and (RL), reflected light. Visitors will note that specimens captured using the various techniques available with the MIC-D microscope behave differently during image processing in the tutorial.
Adjacent to the Specimen Image window is a Spatial Resolution window that displays the captured image at varying resolutions, which are selectable with the Pixel Dimensions slider. To operate the tutorial, select an image from the Choose A Specimen pull-down menu, and vary the pixel dimensions (and spatial resolution) with the Pixel Dimensions slider (which assumes a random default position when the tutorial is initialized). The number of pixels utilized in the horizontal and vertical axes of the image is presented directly beneath the slider, as is the total number of pixels employed in the entire image composition.
The Olympus MIC-D digital microscope contains a CMOS active pixel image sensor having pixel dimensions of 7.6 square microns, which produces a corresponding image area of 4.86 x 3.64 millimeters on the surface of the photodiode array. The resulting digital image size is 640 x 480 pixels, which equals 326,688 individual pixels. The ultimate resolution of the CMOS image sensor is a function of the number of photodiodes and their size relative to the image projected onto the surface of the array by the microscope optics. Acceptable resolution of a specimen imaged with the MIC-D digital microscope can only be achieved if at least two samples are made for each resolvable unit. Numerical aperture of the MIC-D microscope ranges from approximately 0.05 at the lowest optical magnification (0.7x) to about 0.17 at the highest magnification (9x). Considering an average visible light wavelength of 550 nanometers and an optical resolution range between 1.5 and 7 microns (depending upon magnification), the MIC-D CMOS sensor pixel size is adequate to capture all of the detail present in most specimens at intermediate to high magnifications without significant sacrifice in resolution.
When operating the tutorial, as the Pixel Dimensions slider is moved to the right, the spatial frequency of the digital image is linearly reduced. The spatial frequencies utilized range from 175 x 175 pixels (30,625 total pixels) down to 7 x 7 pixels (49 total pixels) to provide a wide latitude of possible resolutions within the frequency domain. As the slider is moved to the right (reducing the number of pixels in the digital image), specimen details are sampled at increasingly lower spatial frequencies and image detail is lost. At the lower spatial frequencies, pixel blocking occurs (often referred to as pixelation) and masks most of the image features.
The spatial resolution of a digital image is related to the spatial density of the image and optical resolution of the microscope used to capture the image. The number of pixels contained in a digital image and the distance between each pixel (known as the sampling interval) are a function of the accuracy of the digitizing device. The optical resolution is a measure of the microscope's ability to resolve the details present in the original specimen, and is related to the quality of the optics, sensor, and electronics in addition to the spatial density (the number of pixels in the digital image). In situations where the optical resolution of the microscope is superior to the spatial density, then the spatial resolution of the resulting digital image is limited only by the spatial density.
All details contained in a digital image, ranging from very coarse to extremely fine, are composed of brightness transitions that cycle between various levels of light and dark. The cycle rate between brightness transitions is known as the spatial frequency of the image, with higher rates corresponding to higher spatial frequencies. Varying levels of brightness in specimens observed through the microscope are common, with the background usually consisting of a uniform intensity and the specimen exhibiting a spectrum of brightness levels. In areas where the intensity is relatively constant (such as the background), the spatial frequency varies only slightly across the viewfield. In contrast, many specimen details often exhibit extremes of light and dark with a wide gamut of intensities in between.
The numerical value of each pixel in the digital image represents the intensity of the optical image averaged over the sampling interval. Thus, background intensity will consist of a relatively uniform mixture of pixels, while the specimen will often contain pixels with values ranging from very dark to very light. The ability of a digital camera system to accurately capture all of these details is dependent upon the sampling interval. Features seen in the microscope that are smaller than the digital sampling interval (have a high spatial frequency) will not be represented accurately in the digital image. The Nyquist criterion requires a sampling interval equal to twice the highest specimen spatial frequency to accurately preserve the spatial resolution in the resulting digital image. An equivalent measure is Shannon's sampling theorem, which states that the digitizing device must utilize a sampling interval that is no greater than one-half the size of the smallest resolvable feature of the optical image. Therefore, to capture the smallest degree of detail present in a specimen, sampling frequency must be sufficient so that two samples are collected for each feature, guaranteeing that both light and dark portions of the spatial period are gathered by the imaging device.
If sampling of the specimen occurs at an interval beneath that required by either the Nyquist criterion or Shannon theorem, details with high spatial frequency will not be accurately represented in the final digital image. In the optical microscope, the Abbe limit of resolution for optical images is 0.22 micrometers, meaning that a digitizer must be capable of sampling at intervals that correspond in the specimen space to 0.11 micrometers or less. A digitizer that samples the specimen at 512 points per horizontal scan line would produce a maximum horizontal field of view of about 56 micrometers (512 x 0.11 micrometers). If too few pixels are utilized in sample acquisition, then all of the spatial details comprising the specimen will not be present in the final image. Conversely, if too many pixels are gathered by the imaging device (often as a result of excessive optical magnification), no additional spatial information is afforded, and the image is said to have been oversampled. The extra pixels do not theoretically contribute to the spatial resolution, but can often help improve the accuracy of feature measurements taken from a digital image. To ensure adequate sampling for high-resolution imaging, an interval of 2.5 to 3 samples for the smallest resolvable feature is suggested.
A majority of digital cameras coupled to modern microscopes have a fixed minimum sampling interval, which cannot be adjusted to match the specimen's spatial frequency. It is important to choose a camera and digitizer combination that can meet the minimum spatial resolution requirements of the microscope magnification and specimen features. If the sampling interval exceeds that necessary for a particular specimen, the resulting digital image will contain more data than is needed, but no spatial information will be lost.
Kenneth R. Spring - Scientific Consultant, Lusby, Maryland, 20657.
John C. Russ - Materials Science and Engineering Department, North Carolina State University, Raleigh, North Carolina, 27695.
Matthew J. Parry-Hill and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.
Questions or comments? Send us an email.
© 1995-2019 by Michael W. Davidson and The Florida State University. All Rights Reserved. No images, graphics, software, scripts, or applets may be reproduced or used in any manner without permission from the copyright holders. Use of this website means you agree to all of the Legal Terms and Conditions set forth by the owners.
This website is maintained by our