The ability to resolve different objects in the displayed CT image, when the difference in attenuation between the objects and the background is large compared to noise; normally a difference corresponding to at least one hundred HU is considered adequate.
The number of points per unit length into which an image is divided. For example, 200 dots per inch (dpi).
The number of pixels in the horizontal and vertical dimensions used to represent a digital image.
Defines the smallest feature that can be detected in an image. This is usually defined as line pairs per mm.
Describes how much detail in a photographic image is visible to the human eye. High-resolution images are sharp and more details are visible.
the ability to define minute adjacent objects/points in an image, generally measured in line pairs per mm (lp/mm).
Spatial resolution refers to the area on the ground that an imaging system, such as a satellite sensor, can distinguish. There are many measures of spatial resolution, the most common include the Instantaneous Field of View (IFOV), and the Effective Instantaneous Field of View (EIFOV).
The spacing between points in a field, such as the spacing between soil sampling points. The closer the points are to one another, the higher the spatial resolution.
Roughly speaking, the degree to which fine detail can be seen in an image. More precisely, resolution is the smallest distance between two objects that can be barely distinguished in the data. Note that if the resolution is limited by pixel size (which is the usual case in vegetation remote sensing), pixel size (in meters) is not the same as resolution. For example, suppose two bright, sub-pixel objects on a dark background are sampled in a square grid detector array. If one object occurs in the lower left corner of a pixel, and the second object occurs in the upper right corner of a pixel to the upper right of the first pixel, these two objects are not resolved (the data would still just show a two-pixel blob against a dark background). Any further apart, however, and they would be resolved. So if the pixel size is d×d meters, the scale of the finest object that can be resolved (r) in the image is actually given by r2=(2d)2+(2d)2, i.e. r~2.8d.
Size of the smallest object that can be distinguished by a remote sensing device.
Number of pixels horizontally and vertically in a digital image.
The area of the ground surface corresponding to a pixel in a satellite image.
The level of spatial detail depicted in an image.
The ability to form separable images of close objects.
The ability to sharply and clearly define the extent or shape of features within an image. It describes how close two features can be within an image and still be resolved as unique..
the spatial resolution of a PET system represents its ability to distinguish between two points after image reconstruction
Measures the smallest object/area that can be seen by a satellite. It is the size of a single pixel in the satellite's image, and ranges from kilometers down to meters.
The sharpness of an image usually measured in line pairs per mm.
the size of the smallest unit that can be identified by a remote sensing observation.
The smallest spatial detail in an image that can be resolved. Spatial resolution is described in a variety of ways, including the IFOV or the Airy disk size (both previously defined). As a broad generalization, spatial resolution is sometimes described in terms of the number of pixels in the imager array (angular FOV of the lens and the range to the target must also be considered).
a measure of the detail captured in a digital image (represented by dots per inch)
Resolution is important in the ability to recognize and distinguish features. For raster data, the spatial resolution is the size of each grid-cell or pixel. For example, the VEMAP2 collection is made up of raster data for the USA at 0.5 degree latitude by longitude resolution. This means that the USA is divided into 0.5 degree grid-cells and each grid-cell is represented by a single data value. For vector data, the spatial resolution is the precision at which the location and shape of geographic features are stored. For example, a resolution of 1 meter means that the true ground position of a coordinate is within one meter of the stored coordinate values.
