Comparative dimensions of sensor sizes

In digital photography, the image sensor format is the shape and size of the image sensor.

The image sensor format of a digital camera determines the angle of view of a particular lens when used with a particular camera. In particular, image sensors in digital SLR cameras tend to be smaller than the 24 mm × 36 mm image area of full-frame 35 mm cameras, and therefore lead to a narrower angle of view.

Lenses produced for 35 mm film cameras may mount well on the digital bodies, but the larger image circle of the 35 mm system lens allows unwanted light into the camera body, and the smaller size of the image sensor compared to 35 mm format results in cropping of the image compared to the results produced on the film camera. This latter effect is known as field-of-view crop; the format size ratio is known as the field of view crop factor, crop factor for short, or focal-length multiplier.

Sensor size and depth of field[link]

Three possible depth of field comparisons between formats are discussed, applying the formulae derived in the article on depth of field. The depths of field of the three cameras may be the same, or different in either order, depending on what is held constant in the comparison.

Considering a picture with the same subject distance and angle of view for two different formats:

Failed to parse (Missing texvc executable; please see math/README to configure.): \frac {\mathrm{DOF}_2} {\mathrm{DOF}_1} \approx \frac {d_1} {d_2}

so the DOFs are in inverse proportion to the absolute aperture diameters Failed to parse (Missing texvc executable; please see math/README to configure.): d_1

and Failed to parse (Missing texvc executable; please see math/README to configure.): d_2

.

Using the same absolute aperture diameter for both formats with the “same picture” criterion (equal angle of view, magnified to same final size) yields the same depth of field. It is equivalent to adjusting the f-number inversely in proportion to crop factor – a smaller f-number for smaller sensors. (This also means that, when holding the shutter speed fixed, the exposure is changed by the adjustment of the f-number required to equalise depth of field. But the aperture area is held constant, so sensors of all sizes receive the same total amount of light energy from the subject. The smaller sensor is then operating at a lower ISO setting, by the square of the crop factor.)

And, we might compare the depth of field of sensors receiving the same photometric exposure – the f-number is fixed instead of the aperture diameter – the sensors are operating at the same ISO setting in that case, but the smaller sensor is receiving less total light, by the area ratio. The ratio of depths of field is then

Failed to parse (Missing texvc executable; please see math/README to configure.): \frac {\mathrm{DOF}_2} {\mathrm{DOF}_1} \approx \frac {l_1} {l_2}

where Failed to parse (Missing texvc executable; please see math/README to configure.): l_1

and Failed to parse (Missing texvc executable; please see math/README to configure.): l_2
are the characteristic dimensions of the format, and thus Failed to parse (Missing texvc executable; please see math/README to configure.): l_1/l_2
is the relative crop factor between the sensors. It is this result that gives rise to the common opinion that small sensors yield greater depth of field than large ones.

An alternative is to consider the depth of field given by the same lens in conjunction with different sized sensors (changing the angle of view). The change in depth of field is brought about by the requirement for a different degree of enlargement to achieve the same final image size. In this case the ratio of depths of field becomes

Failed to parse (Missing texvc executable; please see math/README to configure.): \frac {\mathrm{DOF}_2} {\mathrm{DOF}_1} \approx \frac {l_2} {l_1}

.

Sensor size, noise and dynamic range[link]

Discounting pixel response non-uniformity (PRNU), which is not intrinsically sensor-size dependent, the noises in an image sensor are photon shot noise, read noise, and dark noise. The overall signal to noise ratio of a sensor (SNR), observed at the scale of a single pixel, is

Failed to parse (Missing texvc executable; please see math/README to configure.): \mathrm{SNR} = \frac{P Q_e t}{\sqrt{P Q_e t + D t + N_r^2}}

where Failed to parse (Missing texvc executable; please see math/README to configure.): P

is the incident photon flux (photons per second in the area of a pixel), Failed to parse (Missing texvc executable; please see math/README to configure.): Q_e
is the quantum efficiency, Failed to parse (Missing texvc executable; please see math/README to configure.): t
is the exposure time, Failed to parse (Missing texvc executable; please see math/README to configure.): D
is the pixel dark current in electrons per second and Failed to parse (Missing texvc executable; please see math/README to configure.): N_r
is the pixel read noise in electrons.[1]

Each of these noises has a different dependency on sensor size.

Exposure and photon flux[link]

Image sensor noise can be compared across formats for a given fixed photon flux per pixel area (the P in the formulas); this analysis is useful for a fixed number of pixels with pixel area proportional to sensor area, and fixed absolute aperture diameter for a fixed imaging situation in terms of depth of field, diffraction limit at the subject, etc. Or it can be compared for a fixed focal-plane illuminance, corresponding to a fixed f-number, in which case P is proportional to pixel area, independent of sensor area. The formulas above and below can be evaluated for either case.

Shot noise[link]

In the above equation, the shot noise SNR is given by

Failed to parse (Missing texvc executable; please see math/README to configure.): \frac{P Q_e t}{\sqrt{P Q_e t}} = \sqrt{P Q_e t}

.

Apart from the quantum efficiency it depends on the incident photon flux and the exposure time,which is equivalent to the exposure and the sensor area; since the exposure is the integration time multiplied with the image plane illuminance, and illuminance is the luminous flux per unit area. Thus for equal exposures, the signal to noise ratios of two different size sensors of equal quantum efficiency and pixel count will (for a given final image size) be in proportion to the square root of the sensor area (or the linear scale factor of the sensor). If the exposure is constrained by the need to achieve some required depth of field (with the same shutter speed) then the exposures will also be in relation to the square root of the sensor area, producing the interesting result that if depth of field is a constraint, image shot noise is not dependent on sensor area.

Read noise[link]

The read noise is the total of all the electronic noises in the conversion chain for the pixels in the sensor array. To compare it with photon noise, it must be referred back to its equivalent in photoelectrons, which requires the division of the noise measured in volts by the conversion gain of the pixel. This is given, for an active pixel sensor, by the voltage at the input (gate) of the read transistor divided by the charge which generates that voltage, Failed to parse (Missing texvc executable; please see math/README to configure.): CG = V_{rt}/Q_{rt} . This is the inverse of the capacitance of the read transistor gate (and the attached floating diffusion) since capacitance Failed to parse (Missing texvc executable; please see math/README to configure.): C = Q/V .^[2] Thus Failed to parse (Missing texvc executable; please see math/README to configure.): CG = 1/C_{rt} .

In general for a planar structure such as a pixel, capacitance is proportional to area, therefore the read noise scales down with sensor area, as long as pixel area scales with sensor area, and that scaling is performed by uniformly scaling the pixel.

Considering the signal to noise ratio due to read noise at a given exposure, the signal will scale as the sensor area along with the read noise and therefore read noise SNR will be unaffected by sensor area. In a depth of field constrained situation, the exposure of the larger sensor will be reduced in proportion to the sensor area, and therefore the read noise SNR will reduce likewise.

Dark noise[link]

The dark current contributes two kinds of noise: dark offset, which is only partly correlated between pixels, and the shot noise associated with dark offset, which is uncorrelated between pixels. Only the shot-noise component Dt is included in the formula above, since the uncorrelated part of the dark offset is hard to predict, and the correlated or mean part is relatively easy to subtract off. The mean dark current contains contributions proportional both to the area and the linear dimension of the photodiode, with the relative proportions and scale factors depending on the design of the photodiode.^[3] Thus in general the dark noise of a sensor may be expected to rise as the size of the sensor increases. However, in most sensors the mean pixel dark current at normal temperatures is small, lower than 50 e- per second,^[4] thus for typical photographic exposure times dark current and its associated noises may be discounted. At very long exposure times, however, it may be a limiting factor. And even at short or medium exposure times, a few outliers in the dark-current distribution may show up as "hot pixels".

Dynamic range[link]

Dynamic range is the ratio of the largest and smallest recordable signal, the smallest being typically defined by the 'noise floor'. In the image sensor literature, the noise floor is taken as the readout noise, so Failed to parse (Missing texvc executable; please see math/README to configure.): DR = Q_{max} / \sigma_{readout} ^[5] (note, the read noise Failed to parse (Missing texvc executable; please see math/README to configure.): \sigma_{readout}

is the same quantity as Failed to parse (Missing texvc executable; please see math/README to configure.): N_r
referred to in[1])

The measurement here is made at the level of a pixel (which strictly means that the DR of sensors with different pixel counts is measured over a different spatial bandwidth, and cannot be compared without normalisation). If we assume sensors with the same pixel count but different sizes, then the pixel area will be in proportion to the sensor area. If the maximum exposure (amount of light per unit area) is the same then both the maximum signal and the read noise reduce in proportion to the pixel (and therefore the sensor) area, so the DR does not change. If the comparison is made according to DOF limited conditions, so that the exposure of the larger sensor is reduced in proportion to the area of the sensor (and pixel, for sensors with equal pixel count) then Failed to parse (Missing texvc executable; please see math/README to configure.): Q_{max}

is constant, and the read noise (Failed to parse (Missing texvc executable; please see math/README to configure.): \sigma_{readout}

) falls with the sensor area, leading to a higher dynamic range for the smaller sensor. Summarising the above discussion, considering separately the parts of the image signal to noise ratio due to photon shot noise and read noise and their relation to the linear sensor size ratio or 'crop factor' (remembering that conventionally crop factor increases as the sensor gets smaller) then:

It should be noted that this discussion isolates the effects of sensor scale on SNR and DR, in reality there are many other factors which affect both these quantities.

Sensor size and diffraction[link]

The resolution of all optical systems is limited by diffraction. One way of considering the effect that diffraction has on cameras using different sized sensors is to consider the modulation transfer function (MTF) due to diffraction, which will contribute a factor to the overall system MTF along with the other factors, typically the MTFs of the lens, anti-aliasing filter and sensor sampling window.^[6] The spatial cut-off frequency due to diffraction through a lens aperture is

Failed to parse (Missing texvc executable; please see math/README to configure.): \xi_\mathrm{cutoff}=\frac{1}{\lambda N}

where λ is the wavelength of the light passing through the system and N is the f-number of the lens. If that aperture is circular, as are (approximately) most photographic apertures, then the MTF is given by

Failed to parse (Missing texvc executable; please see math/README to configure.): \mathrm{MTF}(\xi / \xi_\mathrm{cutoff})=\frac{2}{\pi} \left \{ \cos^{-1}(\xi / \xi_\mathrm{cutoff})-(\xi / \xi_\mathrm{cutoff})\left [ 1-( \xi / \xi_\mathrm{cutoff})^2 \right ]^{1/2} \right \}

for Failed to parse (Missing texvc executable; please see math/README to configure.): \xi < \xi_\mathrm{cutoff}

and Failed to parse (Missing texvc executable; please see math/README to configure.):  0 
for Failed to parse (Missing texvc executable; please see math/README to configure.):  \xi \ge \xi_\mathrm{cutoff} 

^[7] The diffraction based factor of the system MTF will therefore scale according to Failed to parse (Missing texvc executable; please see math/README to configure.): \xi_\mathrm{cutoff}

and in turn according to Failed to parse (Missing texvc executable; please see math/README to configure.):  1/N 
(for the same light wavelength). 

In considering the effect of sensor size, and its effect on the final image, the different magnification required to obtain the same size image for viewing must be accounted for, resulting in an additional scale factor of Failed to parse (Missing texvc executable; please see math/README to configure.): 1/{C}

where Failed to parse (Missing texvc executable; please see math/README to configure.): {C}
is the relative crop factor, making the overall scale factor Failed to parse (Missing texvc executable; please see math/README to configure.): 1 / (N C)

. Considering the three cases above:

For the 'same picture' conditions, same angle of view, subject distance and depth of field, then the F-numbers are in the ratio Failed to parse (Missing texvc executable; please see math/README to configure.): 1/C , so the scale factor for the diffraction MTF is 1, leading to the conclusion that the diffraction MTF at a given depth of field is independent of sensor size.

In both the 'same photometric exposure' and 'same lens' conditions, the F-number is not changed, and thus the spatial cutoff and resultant MTF on the sensor is unchanged, leaving the MTF in the viewed image to be scaled as the magnification, or inversely as the crop factor.

Sensor format and lens size[link]

It might be expected that lenses appropriate for a range of sensor sizes could be produced by simply scaling the same designs in proportion to the crop factor.^[8] Such an exercise would in theory produce a lens with the same F-number and angle of view, with a size proportional to the sensor crop factor. In practice, simple scaling of lens designs is not always achievable, due to factors such as the non-scalability of manufacturing tolerance, structural integrity of glass lenses of different sizes and available manufacturing techniques and costs. Moreover, to maintain the same absolute amount of information in an image (which can be measured as the space bandwidth product^[9]) the lens for a smaller sensor requires a greater resolving power. The development of the 'Tessar' lens is discussed by Nasse,^[10] and shows its transformation from an f/6.3 lens for plate cameras using the original three-group configuration through to an f/2.8 5.2 mm four-element optic with eight extremely aspheric surfaces, economically manufacturable because of its small size. Its performance is 'better than the best 35 mm lenses – but only for a very small image'.

In summary, as sensor size reduces, the accompanying lens designs will change, often quite radically, to take advantage of manufacturing techniques made available due to the reduced size. The functionality of such lenses can also take advantage of these, with extreme zoom ranges becoming possible. These lenses are often very large in relation to sensor size, but with a small sensor can be fitted into a compact package.

Sensor size and shading effects[link]

Semiconductor image sensors can suffer from shading effects at large apertures and at the periphery of the image field, due to the geometry of the light cone projected from the exit pupil of the lens to a point, or pixel, on the sensor surface. The effects are discussed in detail by Catrysse and Wandell .^[11] In the context of this discussion the most important result from the above is that to ensure a full transfer of light energy between two coupled optical systems such as the lens' exit pupil to a pixel's photoreceptor the geometrical extent (also known as etendue or light throughput) of the objective lens / pixel system must be smaller than or equal to the geometrical extent of the microlens / photoreceptor system. The geometrical extent of the objective lens / pixel system is given by

Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{objective} \simeq \frac{w_\mathrm{pixel}}{2{(f/\#)}_\mathrm{objective}}

,

where w_pixel is the width of the pixel and (f/#)_objective is the f-number of the objective lens. The geometrical extent of the microlens / photoreceptor system is given by

Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{pixel} \simeq \frac{w_\mathrm{photoreceptor}}{2{(f/\#)}_\mathrm{microlens}}

,

where w_{photoreceptor} is the width of the photoreceptor and (f/#)_microlens is the f-number of the microlens.

So to avoid shading,

Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{pixel} \ge G_\mathrm{objective}

, therefore Failed to parse (Missing texvc executable; please see math/README to configure.): \frac{w_\mathrm{photoreceptor}}{{(f/\#)}_\mathrm{microlens}} \ge \frac{w_\mathrm{pixel}}{{(f/\#)}_\mathrm{objective}}

If w_{photoreceptor} / w_pixel = ff, the linear fill factor of the lens, then the condition becomes

Failed to parse (Missing texvc executable; please see math/README to configure.): {(f/\#)}_\mathrm{microlens} \le {(f/\#)}_\mathrm{objective} \times \mathit{ff}

Thus if shading is to be avoided the f-number of the microlens must be smaller than the f-number of the taking lens by at least a factor equal to the linear fill factor of the pixel. The f-number of the microlens is determined ultimately by the width of the pixel and its height above the silicon, which determines its focal length. In turn, this is determined by the height of the metallisation layers, also known as the 'stack height'. For a given stack height, the f-number of the microlenses will increase as pixel size reduces, and thus the objective lens f-number at which shading occurs will tend to increase. This effect has been observed in practice, as recorded in the DxOmark article 'F-stop blues'^[12]

In order to maintain pixel counts smaller sensors will tend to have smaller pixels, while at the same time smaller objective lens f-numbers are required to maximise the amount of light projected on the sensor. To combat the effect discussed above, smaller format pixels include engineering design features to allow the reduction in f-number of their microlenses. These may include simplified pixel designs which require less metallisation, 'light pipes' built within the pixel to bring its apparent surface closer to the microlens and 'back side illumination' in which the wafer is thinned to expose the rear of the photodetectors and the microlens layer is placed directly on that surface, rather than the front side with its wiring layers. The relative effectiveness of these stratagems is discussed by Aptina in some detail.^[13]

Common image sensor formats[link]

Sizes of the sensors used in most current digital cameras relative to a standard 35mm frame.

Medium-format digital sensors[link]

The most common sensor size for medium-format digital cameras is approximately 48 × 36 mm (1.9 × 1.4 in)^{[citation needed]}, due to the widespread use of Kodak's 22-megapixel KAF-22000 and 39-megapixel KAF-39000^[14] CCDs in that format. Phase one offers the P65+ digital back with Dalsa's 53.9 × 40.4 mm (2.12 × 1.59 in) sensor containing 60.5 megapixels^[15] and Leica offers an "S-System" DSLR with a 45 × 30 mm (1.8 × 1.2 in) sensor containing 37-megapixels.^[16] In 2010, Pentax released the 40MP 645D medium format DSLR with a 44 × 33 mm (1.7 × 1.3 in) sensor.^[17]

Sensors equipping most DSLRs and mirrorless interchangeable-lens cameras[link]

Some professional DSLRs use full-frame sensors, equal to the size of a frame of 35 mm film.

Most consumer-level DSLRs and MILCs/EVILs use relatively large sensors, either around the size of a frame of APS-C film, with a crop factor of 1.5-1.6; or 30% smaller than that, with a crop factor of 2.0 (this is the Four Thirds System, adopted by Olympus and Panasonic).

On September 2011, Nikon announced their new format CX, whose size is 1" (2.7 crop factor).^[18] It has been adopted for the Nikon 1 camera system (Nikon J1 and V1 models). As of September 2011^[update] there is only one MILC model equipped with a very small sensor, typical of compact cameras: it is the Pentax Q, equipped with a 1/2.3" sensor (5.62 crop factor). See Sensors equipping Compact digital cameras and camera-phones section below.

Many different terms are used in marketing to describe DSRL/MILC sensor formats, including the following:

• Full-frame digital SLR format, with sensor dimensions nearly equal to those of 35 mm film (36 × 24 mm)
• Canon's APS-H format for high-speed pro-level DSLRs (crop factor 1.3)
• Leica's M8 and M8.2 sensor (crop factor 1.33).
• APS-C refers to a range of similarly-sized formats, including
  • Nikon, Pentax, Samsung, Konica Minolta/Sony, Fujifilm, Epson (crop factor 1.5)
  • Canon entry-level DSLR formats (crop factor 1.6)
• Foveon X3 format used in Sigma SD-series DSLRs and DP-series mirrorless (crop factor 1.7)
• Four Thirds System format (crop factor 2.0)
• Nikon CX format used in Nikon 1 series (crop factor 2.7)

Production costs for a full frame sensor can exceed twenty times the costs of an APS-C sensor. Only about thirty full-frame sensors can be produced on an 8 inches (20 cm) silicon wafer that would fit 112 APS-C sensors, and there is a significant reduction in yield due to the large area for contaminants per component. Additionally, the full frame sensor requires three separate exposures during the photolithography stage, which requires separate masks and quality control steps. The APS-H size was selected since it is the largest that can be imaged with a single mask to help control production costs and manage yields.^[19]

Due to the ever-changing constraints of semiconductor fabrication and processing, and because camera manufacturers often source sensors from third-parties foundries, it is common for sensor dimensions to vary slightly within the same nominal format. For example, the Nikon D3 and D700 cameras' nominally full-frame sensors actually measure 36 × 23.9 mm, slightly smaller than a 36 × 24 mm frame of 35 mm film. As another example, the Pentax K200D's sensor (made by Sony) measures 23.5 × 15.7 mm, while the contemporaneous K20D's sensor (made by Samsung) measures 23.4 × 15.6 mm.

Most DSLR image sensor formats approximate the 3:2 aspect ratio of 35 mm film. Again, the Four Thirds System is a notable exception, with an aspect ratio of 4:3 as seen in most compact digital cameras (see below).

Sensors equipping compact digital cameras and camera-phones[link]

Most image sensors equipping compact cameras have an aspect ratio of 4:3. This matches the aspect ratio of the popular SVGA, XGA, and SXGA display resolutions at the time of the first digital cameras, allowing images to be displayed on usual monitors without cropping.

As of December 2010^[update] most compact digital cameras used 1/2.3" or even small 1/2.33" sensors. 1/2.3"-sensor digital cameras include the Canon Powershot SX230 IS, the Fuji Finepix Z90, and the Nikon Coolpix S9100. Older digital cameras with a 1/2.5" sized sensor (used mostly from 2005–2010) include the Panasonic Lumix DMC-FS62, Canon Powershot SX120 IS, Sony CyberShot DSC-S700, and Casio Exilim EX-Z80.

As of 2012^[update] most bridge cameras, including the Sony CyberShot DSC-HX100V and the Canon PowerShot SX40 HS, use a 1/2.3" sensor. The high-end bridge camera Fuji XS-1, though, is equipped with a much larger sensor (2/3" – twice the area of a typical bridge-camera sensor ).

High-end compact cameras using sensors of nearly twice the area than those adopted for common compacts include Canon PowerShot G12 (1/1.7") and Powershot S90/S95 (1/1.7"), Ricoh GR Digital IV (1/1.7"), Nikon Coolpix P7100 (1/1.7"), Panasonic DMC-LX5 (1/1.63") and Olympus XZ-1(1/1.63"). The Fujifilm FinePix X-10 has a 2/3" sensor, possibly the largest sensor on a camera which is still labelled "compact" despite weighing 353 grams. In January 2012 Canon announced the PowerShot G1X, equipped with a relative huge 1.5" sensor (larger than the 4/3" sensor adopted by some compact DSLR). Many^[who?] (starting with Canon itself) refer to it as "compact", but weighing 534 grams G1X is actually a bridge camera rather than a compact .

The sensors of camera phones are typically much smaller than those of typical compact cameras, allowing greater miniaturization of the electrical and optical components. Sensor sizes of around 1/6" are common in camera phones, webcams and digital camcorders. The Nokia N8's 1/1.83" sensor was the largest in a phone in late 2011. The upcoming Nokia 808 surpasses compact cameras with its 41 million pixels, 1/1.2" sensor.^[20]

Table of sensor formats and sizes[link]

Sensor formats of digital cameras are mostly expressed in the non-standardized "inch" system as approximately 1.5 times the length of the diagonal of the sensor. This goes back to the way image sizes of video cameras used until the late 1980s were expressed, referring to the outside diameter of the glass envelope of the video camera tube. David Pogue of the New York Times states that "the actual sensor size is much smaller than what the camera companies publish – about one-third smaller." For example, a camera advertising a 1/2.7" sensor does not have a sensor with a diagonal of 0.37"; instead, the diagonal is closer to 0.26".^[21][22] Instead of "formats", these sensor sizes are often called types, as in "1/2-inch-type CCD."

Due to inch-based sensor formats being not standardized, their exact dimensions may vary, but those listed are typical.^[22] The listed sensor areas span more than a factor of 1000 and are proportional to the maximum possible collection of light and image resolution (same lens speed, i.e., maximum aperture), but in practice are not directly proportional to image noise or resolution due to other limitations. See comparisons.^[23][24]

Bridging the gap in sensor sizes[link]

This unreferenced section requires citations to ensure verifiability.

This semi-logarithmic graph shows the large gap which – for a long time and until Sep. 2011 – existed between compact digital and DSLR camera sensor sizes. The x axis is a discrete set of sensor format sizes used in digital cameras, not a linear measurement axis.

From 2005 there was an increasing interest in producing medium-sized cameras with large sensors but without the moving mirror systems, and consequently the bulk, typical of DSLR camera bodies.

Manufacturers gradually responded to this interest, which led to a new type: the mirrorless interchangeable-lens camera. Epson, an early entrant, introduced the R-D1, a digital rangefinder using the Leica M mount. Other companies followed suit, by introducing similar cameras that focus electronically rather than manually (such as Olympus, with its PEN series; Panasonic, with its G and GF series; Sony, with its Nex series; Samsung, with its NX series). MILC cameras might overall look like compact digital ones, with at least two notable differences: a sensor in most cases of the size found in digital SLRs, and interchangeable lenses. The latter feature, though, was incorporated in at least one small-sensor camera as well (Pentax Q, announced in June 2011).

Nonetheless, until 2011 there still remained a large gap in sensor sizes between digital compact cameras on the one hand and DSLRs/MILCs on the other. Compact cameras were all equipped with sensors smaller than 1/1.6" (48.5 mm²), whereas 4/3" (225 mm²) was the smallest sensor to be found on DSLRs/MILCs. Noticeable exceptions – for a few years – had been Olympus E-10 and E-20 (large, semi-professional hybrid cameras announced in the early 2000s and equipped with a 2/3" sensor). The main reason for such size-gap was portability: large sensors require bulky lenses (that's why MILC cameras with large sensors often show a marked disproportion between their tiny bodies and their large lens systems, zoom objectives especially).

That sensor-size gap was bridged by camera models announced in September 2011: on the compact side of the gap, a very large (for a compact) 2/3" (58.1 mm²) sensor equipped the high-end Fuji X10 compact. Almost at the same time, on the DSLR/MILC side of the divide, Nikon announced the Nikon 1 system, built around a new sensor format they named 'CX' (13.2mm × 8.8mm, roughly 1" in the inch system).

With such format additions – the 'CX' especially – the crop-factor difference between the largest compact camera sensor (2/3", 3.9 crop factor) and the smallest MILC sensor (1", 2.7 crop factor) is now about one half the gap previously existing between 1/1.6" and 4/3" sensors.

See also[link]

• Full-frame digital SLR
• Sensor size and angle of view
• 35 mm equivalent focal length
• Film format
• Digital versus film photography
• List of large sensor interchangeable-lens video cameras

Notes and references[link]

External links[link]

• Eric Fossum: Photons to Bits and Beyond: The Science & Technology of Digital, Oct. 13, 2011 (YouTube-Video of lecture)
• Joseph James: Equivalence at Joseph James Photography
• Simon Tindemans: Alternative photographic parameters: a format-independent approach at 21stcenturyshoebox
• Compact Camera High ISO modes: Separating the facts from the hype at dpreview.com, May 2007
• The best compromise for a compact camera is a sensor with 6 million pixels or better a sensor with a pixel size of >3µm at 6mpixel.org

A CCD image sensor on a flexible circuit board

Image sensor on the motherboard of a Nikon Coolpix L2 6 MP

An image sensor is a device that converts an optical image into an electronic signal. It is used mostly in digital cameras, camera modules and other imaging devices. Early analog sensors were video camera tubes, most currently used are digital charge-coupled device (CCD) or complementary metal–oxide–semiconductor (CMOS) active pixel sensors.

CCD vs CMOS[link]

Today, most digital still cameras use either a CCD image sensor or a CMOS sensor. Both types of sensor accomplish the same task of capturing light and converting it into electrical signals.

A CCD image sensor is an analog device. When light strikes the chip it is held as a small electrical charge in each photo sensor. The charges are converted to voltage one pixel at a time as they are read from the chip. Additional circuitry in the camera converts the voltage into digital information.

A CMOS imaging chip is a type of active pixel sensor made using the CMOS semiconductor process. Extra circuitry next to each photo sensor converts the light energy to a voltage. Additional circuitry on the chip may be included to convert the voltage to digital data.

Neither technology has a clear advantage in image quality. On one hand, CCD sensors are more susceptible to vertical smear from bright light sources when the sensor is overloaded; high-end frame transfer CCDs in turn do not suffer from this problem. On the other hand, CMOS sensors are susceptible to undesired effects that come as a result of rolling shutter.

CMOS can potentially be implemented with fewer components, use less power, and/or provide faster readout than CCDs. CCD is a more mature technology and is in most respects the equal of CMOS.^[1][2] CMOS sensors are less expensive to manufacture than CCD sensors.

Another hybrid CCD/CMOS architecture, sold under the name "sCMOS", consists of CMOS readout integrated circuits (ROICs) that are bump bonded to a CCD imaging substrate – a technology that was developed for infrared staring arrays and now adapted to silicon-based detector technology.^[3] Another approach is to utilize the very fine dimensions available in modern CMOS technology to implement a CCD like structure entirely in CMOS technology. This can be achieved by separating individual poly-silicon gates by a very small gap. These hybrid sensors are still in the research phase, and can potentially harness the benefits of both the CCDs and the CMOS imagers.^[4]

Performance[link]

An infrared-blocking filter removed from a Canon EOS 350D DSLR.

There are many parameters that can be used to evaluate the performance of an image sensor, including its dynamic range, its signal-to-noise ratio, its low-light sensitivity, etc. For sensors of comparable types, the signal-to-noise ratio and dynamic range improve as the size increases.

Color separation[link]

There are several main types of color image sensors, differing by the type of color-separation mechanism:

• Bayer sensor, low-cost and most common, using a color filter array that passes red, green, or blue light to selected pixel sensors, forming interlaced grids sensitive to red, green, and blue – the missing color samples are interpolated using a demosaicing algorithm. In order to avoid interpolated color information, techniques like color co-site sampling use a piezo mechanism to shift the color sensor in pixel steps. The Bayer sensors also include back-illuminated sensors, where the light enters the sensitive silicon from the opposite side of where the transistors and metal wires are, such that the metal connections on the devices side are not an obstacle for the light, and the efficiency is higher.^[3][4]
• Foveon X3 sensor, using an array of layered pixel sensors, separating light via the inherent wavelength-dependent absorption property of silicon, such that every location senses all three color channels.
• 3CCD, using three discrete image sensors, with the color separation done by a dichroic prism. Considered the best quality, and generally more expensive than single-CCD sensors.

Specialty sensors[link]

Special sensors are used in various applications such as thermography, creation of multi-spectral images, video laryngoscopes, gamma cameras, sensor arrays for x-rays, and other highly sensitive arrays for astronomy.

Sensors used in digital cameras[link]

Width	Height	Aspect ratio	Actual pixel count	Megapixels	Camera examples
100	100	1:1	10,000	0.01	Kodak (by Steven Sasson) Prototype (1975)
640	480		307,200	0.3	Apple QuickTake 100 (1994)
832	608		505,856	0.5	Canon Powershot 600 (1996)
1,024	768		786,432	0.8	Olympus D-300L (1996)
1024	1024	1:1	1,048,576	1.0	Nikon NASA F4 (1991)
1,280	960		1,228,800	1.3	Fujifilm DS-300 (1997)
1,280	1,024	5:4	1,310,720	1.3	Fujifilm MX-700, Fujifilm MX-1700 (1999), Leica Digilux (1998), Leica Digilux Zoom (2000)
1,600	1,200		1,920,000	2	Nikon Coolpix 950, Samsung GT-S3500
2,012	1,324		2,663,888	2.74	Nikon D1
2,048	1,536		3,145,728	3	Canon PowerShot A75, Nikon Coolpix 995
2,272	1,704		3,871,488	4	Olympus Stylus 410, Contax i4R (although CCD is actually square 2,272x2,272)
2,464	1,648		4,060,672	4.1	Canon 1D
2,560	1,920		4,915,200	5	Olympus E-1, Sony Cyber-shot DSC-F707, Sony Cyber-shot DSC-F717
2,816	2,112		5,947,392	5.9	Olympus Stylus 600 Digital
3,008	2,000		6,016,000	6	Nikon D40, D50, D70, D70s, Pentax K100D, Konica Minolta Maxxum 7D, Konica Minolta Maxxum 5D
3,072	2,048		6,291,456	6.3	Canon EOS 10D, Canon EOS 300D
3,072	2,304		7,077,888	7	Olympus FE-210, Canon PowerShot A620
3,456	2,304		7,962,624	8	Canon EOS 350D
3,264	2,448		7,990,272	8	Olympus E-500, Olympus SP-350, Canon PowerShot A720 IS, Apple iPhone 4S
3,504	2,336		8,185,344	8.2	Canon EOS 30D, Canon EOS-1D Mark II, Canon EOS-1D Mark II N
3,520	2,344		8,250,880	8.25	Canon EOS 20D
3,648	2,736		9,980,928	10	Canon PowerShot G11, Canon PowerShot G12, Canon PowerShot S90, Canon PowerShot S95, Nikon CoolPix P7000, Nikon CoolPix P7100, Olympus E-410, Olympus E-510, Panasonic FZ50, Fujifilm FinePix HS10, Samsung EX1
3,872	2,592		10,036,224	10	Nikon D40x, Nikon D60, Nikon D3000, Nikon D200, Nikon D80, Pentax K10D, Pentax K200D, Sony Alpha A100
3,888	2,592		10,077,696	10.1	Canon EOS 40D, Canon EOS 400D, Canon EOS 1000D
4,064	2,704		10,989,056	11	Canon EOS-1Ds
4,000	3,000		12,000,000	12	Canon Powershot G9, Fujifilm FinePix S200EXR, Nikon Coolpix L110
4,256	2,832		12,052,992	12.1	Nikon D3, Nikon D3S, Nikon D700, Fujifilm FinePix S5 Pro
4,272	2,848		12,166,656	12.2	Canon EOS 450D
4,032	3,024		12,192,768	12.2	Olympus PEN E-P1
4,288	2,848		12,212,224	12.2	Nikon D2Xs/D2X, Nikon D300, Nikon D300S, Nikon D90, Nikon D5000, Pentax K-x
4,900	2,580		12,642,000	12.6	RED ONE Mysterium
4,368	2,912		12,719,616	12.7	Canon EOS 5D
5,120	2,700		13,824,000	13.8	RED Mysterium-X
7,920 (2,640 × 3)	1,760		13,939,200	13.9	Sigma SD14, Sigma DP1 (3 layers of pixels, 4.7 MP per layer, in Foveon X3 sensor)
4,672	3,104		14,501,888	14.5	Pentax K20D, Pentax K-7
4,752	3,168		15,054,336	15.1	Canon EOS 50D, Canon EOS 500D
4,928	3,262		16,075,136	16.1	Nikon D7000, Pentax K-5
4,992	3,328		16,613,376	16.6	Canon EOS-1Ds Mark II, Canon EOS-1D Mark IV
5,184	3,456		17,915,904	17.9	Canon EOS 7D, Canon EOS 60D, Canon EOS 600D, Canon EOS 550D
5,270	3,516		18,529,320	18.5	Leica M9
5,616	3,744		21,026,304	21.0	Canon EOS-1Ds Mark III, Canon EOS-5D Mark II
6,048	4,032		24,385,536	24.4	Sony α 850, Sony α 900, Nikon D3X
7,360	4,912		36,152,320	36.2	Nikon D800
7,500	5,000		37,500,000	37.5	Leica S2
7,212	5,142		39,031,344	39.0	Hasselblad H3DII-39
7,216	5,412		39,052,992	39.1	Leica RCD100
7,264	5,440		39,516,160	39.5	Pentax 645D
7,320	5,484		40,142,880	40.1	Phase One IQ140
7,728	5,368	100:69	41,483,904	41.5	Nokia 808 PureView
8,176	6,132		50,135,232	50.1	Hasselblad H3DII-50, Hasselblad H4D-50
11,250	5,000	9:4	56,250,000	56.3	Better Light 4000E-HS (scanned)
8,956	6,708		60,076,848	60.1	Hasselblad H4D-60
8,984	6,732		60,480,288	60.5	Phase One IQ160, Phase One P65+
10,320	7,752		80,000,640	80	Leaf Aptus-II 12, Leaf Aptus-II 12R
10,328	7,760		80,145,280	80.1	Phase One IQ180
9,372	9,372	1:1	87,834,384	87.8	Leica RC30
12,600	10,500	6:5	132,300,000	132.3	Phase One PowerPhase FX/FX+ (scanned)
18,000	8,000	9:4	144,000,000	144	Better Light 6000-HS/6000E-HS (scanned)
21,250	7,500	17:6	159,375,000	159.4	Seitz 6x17 Digital (scanned)
16,352*	12,264*		200,540,928	200.5	Hasselblad H4D-200MS (*actuated)
18,000	12,000		216,000,000	216	Better Light Super 6K-HS (scanned)
24,000	15,990	2,400:1,599	383,760,000	383.8	Better Light Super 8K-HS (scanned)
30,600	13,600	9:4	416,160,000	416.2	Better Light Super 10K-HS (scanned)
62,830	7,500	6,283:750	471,225,000	471.2	Seitz Roundshot D3 (80 mm lens) (scanned)
62,830	13,500	6,283:1,350	848,205,000	848.2	Seitz Roundshot D3 (110 mm lens) (scanned)
38,000	38,000	1:1	1,444,000,000	1,444	Pan-STARRS PS1
157,000	18,000	157:18	2,826,000,000	2,826	Better Light 300 mm lens Digital (scanned)

Companies[link]

The largest companies that manufacture imaging sensors include the following:

• Agilent
• Aptina
• Canesta
• Canon
• Cypress Semiconductor
• Eastman Kodak
• ESS Technology
• Fujifilm
• MagnaChip
• Matsushita
• Micron Technology
• Mitsubishi
• Nikon
• OmniVision Technologies
• PixArt Imaging
• Pixim
• Samsung
• Sharp
• Sony
• STMicroelectronics
• Toshiba
• TowerJazz
• TransChip
• Trusight

See also[link]

• Video camera tube
• Semiconductor detector
• Full-frame digital SLR
• Image sensor format, the sizes and shapes of common image sensors
• Color filter array, mosaic of tiny color filters over color image sensors
• Sensitometry, the scientific study of light-sensitive materials
• History of television, the development of electronic imaging technology since the 1880s.
• List of large sensor interchangeable-lens video cameras

References[link]

External links[link]

• CCD vs CMOS. Performance comparison
• Digital Camera Sensor Performance Summary by Roger Clark.