Image resolution

Image resolution is the detail an image holds. The term applies to raster digital images, film images, and other types of images. Higher resolution means more image detail.

Image resolution can be measured in various ways. Resolution quantifies how close lines can be to each other and still be visibly resolved. Resolution units can be tied to physical sizes (e.g. lines per mm, lines per inch), to the overall size of a picture (lines per picture height, also known simply as lines, TV lines, or TVL), or to angular subtense. Line pairs are often used instead of lines; a line pair comprises a dark line and an adjacent light line. A line is either a dark line or a light line. A resolution of 10 lines per millimeter means 5 dark lines alternating with 5 light lines, or 5 line pairs per millimeter (5 LP/mm). Photographic lens and film resolution are most often quoted in line pairs per millimeter.

Resolution of digital images

The resolution of digital cameras can be described in many different ways.

Pixel resolution

Resolution is the capability of the sensor to observe or measure the smallest object clearly with distinct boundaries. There is a difference between the resolution and a pixel. A pixel is actually a unit of the digital image. Resolution depends upon the size of the pixel. Usually, with any given lens setting, the smaller the size of the pixel, the higher the resolution will be and the clearer the object in the image will be. Images having smaller pixel sizes might consist of more pixels. The number of pixels correlates to the amount of information within the image.

The term resolution is often used for a pixel count in digital imaging, even though British, American, Japanese, and international standards specify that it should not be so used, at least in the digital camera field.[1][2]

An image of N pixels height by M pixels wide can have any resolution less than N lines per picture height, or N TV lines. But when the pixel counts are referred to as resolution, the convention is to describe the pixel resolution with the set of two positive integer numbers, where the first number is the number of pixel columns (width) and the second is the number of pixel rows (height), for example as 7680 by 6876. Another popular convention is to cite resolution as the total number of pixels in the image, typically given as number of megapixels, which can be calculated by multiplying pixel columns by pixel rows and dividing by one million. Other conventions include describing pixels per length unit or pixels per area unit, such as pixels per inch or per square inch. None of these pixel resolutions are true resolutions, but they are widely referred to as such; they serve as upper bounds on image resolution.

According to the same standards, the number of effective pixels that an image sensor or digital camera has is the count of elementary pixel sensors that contribute to the final image, as opposed to the number of total pixels, which includes unused or light-shielded pixels around the edges.

Below is an illustration of how the same image might appear at different pixel resolutions, if the pixels were poorly rendered as sharp squares (normally, a smooth image reconstruction from pixels would be preferred, but for illustration of pixels, the sharp squares make the point better).

An image that is 2048 pixels in width and 1536 pixels in height has a total of 2048×1536 = 3,145,728 pixels or 3.1 megapixels. One could refer to it as 2048 by 1536 or a 3.1-megapixel image. Or, you can think of it as a very low quality image (72ppi) if printed at about 28.5 inches wide, or a very good quality (300ppi) image if printed at about 7 inches wide.

Unfortunately, the count of pixels isn't a real measure of the resolution of digital camera images, because color image sensors are typically set up to alternate color filter types over the light sensitive individual pixel sensors. Digital images ultimately require a red, green, and blue value for each pixel to be displayed or printed, but one individual pixel in the image sensor will only supply one of those three pieces of information. The image has to be interpolated or demosaiced to produce all three colors for each output pixel.

Spatial resolution

Spatial resolution in radiology refers to the ability of the imaging modality to differentiate two objects. Low spatial resolution techniques will be unable to differentiate between two objects that are relatively close together.

Image at left has a higher pixel count than the one to the right, but is still of worse spatial resolution.

The measure of how closely lines can be resolved in an image is called spatial resolution, and it depends on properties of the system creating the image, not just the pixel resolution in pixels per inch (ppi). For practical purposes the clarity of the image is decided by its spatial resolution, not the number of pixels in an image. In effect, spatial resolution refers to the number of independent pixel values per unit length.

The spatial resolution of computer monitors is generally 72 to 100 lines per inch, corresponding to pixel resolutions of 72 to 100 ppi. With scanners, optical resolution is sometimes used to distinguish spatial resolution from the number of pixels per inch.

In remote sensing, spatial resolution is typically limited by diffraction, as well as by aberrations, imperfect focus, and atmospheric distortion. The ground sample distance (GSD) of an image, the pixel spacing on the Earth's surface, is typically considerably smaller than the resolvable spot size.

In astronomy, one often measures spatial resolution in data points per arcsecond subtended at the point of observation, because the physical distance between objects in the image depends on their distance away and this varies widely with the object of interest. On the other hand, in electron microscopy, line or fringe resolution refers to the minimum separation detectable between adjacent parallel lines (e.g. between planes of atoms), whereas point resolution instead refers to the minimum separation between adjacent points that can be both detected and interpreted e.g. as adjacent columns of atoms, for instance. The former often helps one detect periodicity in specimens, whereas the latter (although more difficult to achieve) is key to visualizing how individual atoms interact.

In Stereoscopic 3D images, spatial resolution could be defined as the spatial information recorded or captured by two viewpoints of a stereo camera (left and right camera). The effects of spatial resolution on overall perceived resolution of an image on a person's mind are yet not fully documented. It could be argued that such "spatial resolution" could add an image that then would not depend solely on pixel count or Dots per inch alone, when classifying and interpreting overall resolution of a given photographic image or video frame.

Spectral resolution

Spectral resolution is the ability to resolve spectral features and bands into their separate components. Color images distinguish light of different spectra. Multispectral images resolve even finer differences of spectrum or wavelength than is needed to reproduce color. That is, multispectral images have higher spectral resolution than normal color images. Spectral resolution is the ability to resolve spectral features and bands into their separate components. The spectral resolution required by the analyst or researcher depends upon the application involved. For example, routine analysis for basic sample identification typically requires low/medium resolution.

Temporal resolution

Temporal resolution (TR) refers to the precision of a measurement with respect to time. Often there is a trade-off between temporal resolution of a measurement and its spatial resolution due to uncertainty principle which is an inherent property of Fourier transform.

Movie cameras and high-speed cameras can resolve events at different points in time. The time resolution used for movies is usually 24 to 48 frames per second (frames/s), whereas high-speed cameras may resolve 50 to 300 frames/s, or even more.

Many cameras and displays offset the color components relative to each other or mix up temporal with spatial resolution:

Radiometric resolution

Radiometric resolution determines how finely a system can represent or distinguish differences of intensity, and is usually expressed as a number of levels or a number of bits, for example 8 bits or 256 levels that is typical of computer image files. The higher the radiometric resolution, the better subtle differences of intensity or reflectivity can be represented, at least in theory. In practice, the effective radiometric resolution is typically limited by the noise level, rather than by the number of bits of representation.

Resolution in various media

This is a list of traditional, analog horizontal resolutions for various media. The list only includes popular formats, not rare formats, and all values are approximate, because the actual quality can vary machine-to-machine or tape-to-tape. For ease-of-comparison, all values are for the NTSC system. (For PAL systems, replace 480 with 576.) Analog formats usually had less chroma resolution.

PPI Pixels cm
800 1000 3.18
300 1000 8.47
200 1000 12.7
72 1000 35.28
PPI Pixels cm
800 3150 10
300 1181 10
200 787 10
72 283 10
PPI Pixels mm Paper size
300 11114x14008 840x1186 A0
300 7016x11114 594x840 A1
300 4961x7016 420x594 A2
300 3508x4961 297x420 A3
300 2480x3508 210x297 A4
300 1748x2480 148x210 A5
300 1240x1748 105x148 A6
300 874x1240 74x105 A7
300 614x874 52x74 A8

See also

References

  1. ↑ Guideline for Noting Digital Camera Specifications in Catalogs. "The term 'Resolution' shall not be used for the number of recorded pixels"
  2. ↑ ANSI/I3A IT10.7000-2004 Photography - Digital Still Cameras - Guidelines for Reporting Pixel-Related Specifications
  3. ↑ http://www.derose.net/steve/resources/video-resolution.html
  4. ↑ Kodak 500t Film spec sheet
  5. ↑ An analysis of film resolution
  6. ↑ Explanation of MTF
  7. 1 2 "/Film Interview: IMAX Executives Talk ‘The Hunger Games: Catching Fire’ and IMAX Misconceptions". Slash Film. December 2, 2013. Retrieved December 17, 2013.
  8. ↑ http://www.phaseone.com/en/camera-systems/iq-series.aspx
  9. ↑ http://www.mamiyaleaf.com/leaf_aptus.html
  10. ↑ http://www.dxomark.com/Cameras/Camera-Sensor-Database/Phase-One/IQ180-Digital-Back
  11. ↑ http://web.forret.com/tools/megapixel.asp?width=10380&height=7816


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