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Image sensor format
Image sensor format
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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 sensor. Because the image sensors in many digital cameras are smaller than the 24 mm × 36 mm image area of full-frame 35 mm cameras, a lens of a given focal length gives a narrower field of view in such cameras.

Sensor size is often expressed as optical format in inches. Other measures are also used; see table of sensor formats and sizes below.

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 film format results in cropping of the image. This latter effect is known as field-of-view crop. The format size ratio (relative to the 35 mm film format) is known as the field-of-view crop factor, crop factor, lens factor, focal-length conversion factor, focal-length multiplier, or lens multiplier.

Sensor size and depth of field

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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:

so the DOFs are in inverse proportion to the absolute aperture diameters and .

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). This condition of equal field of view, equal depth of field, equal aperture diameter, and equal exposure time is known as "equivalence".[1]

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

where and are the characteristic dimensions of the format, and thus 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

.

In practice, if applying a lens with a fixed focal length and a fixed aperture and made for an image circle to meet the requirements for a large sensor is to be adapted, without changing its physical properties, to smaller sensor sizes neither the depth of field nor the light gathering will change.

Sensor size, noise and dynamic range

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Discounting photo response non-uniformity (PRNU) and dark noise variation, which are not intrinsically sensor-size dependent, the noises in an image sensor are shot noise, read noise, and dark noise. The overall signal to noise ratio of a sensor (SNR), expressed as signal electrons relative to rms noise in electrons, observed at the scale of a single pixel, assuming shot noise from Poisson distribution of signal electrons and dark electrons, is

where is the incident photon flux (photons per second in the area of a pixel), is the quantum efficiency, is the exposure time, is the pixel dark current in electrons per second and is the pixel read noise in electrons rms.[2]

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

Exposure and photon flux

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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

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

.

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 be in inverse relation to the sensor area, producing the interesting result that if depth of field is a constraint, image shot noise is not dependent on sensor area. For identical f-number lenses the signal to noise ratio increases as square root of the pixel area, or linearly with pixel pitch. As typical f-numbers for lenses for cell phones and DSLR are in the same range f/1.5–2 it is interesting to compare performance of cameras with small and big sensors. A good 2018 cell phone camera with a typical pixel size of 1.1 μm (Samsung A8) would have about 3 times worse SNR due to shot noise than a 3.7 μm pixel interchangeable lens camera (Panasonic G85) and 5 times worse than a 6 μm full frame camera (Sony A7 III). Taking into consideration the dynamic range makes the difference even more prominent. As such the trend of increasing the number of "megapixels" in cell phone cameras during last 10 years was caused rather by marketing strategy to sell "more megapixels" than by attempts to improve image quality.

Read noise

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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, . This is the inverse of the capacitance of the read transistor gate (and the attached floating diffusion) since capacitance .[3] Thus .

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

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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.[4] 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,[5] 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". Typically, for astrophotography applications sensors are cooled to reduce dark current in situations where exposures may be measured in several hundreds of seconds.

Dynamic range

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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 [6] (note, the read noise is the same quantity as referred to in the SNR calculation[2]).

Sensor size and diffraction

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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). Diffraction is one of the factors that contribute to the overall system MTF. Other factors are typically the MTFs of the lens, anti-aliasing filter and sensor sampling window.[7] The spatial cut-off frequency due to diffraction through a lens aperture is

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

for and for [8] The diffraction based factor of the system MTF will therefore scale according to and in turn according to (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 where is the relative crop factor, making the overall scale factor . 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 , 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

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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.[9] 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[10]) the lens for a smaller sensor requires a greater resolving power. The development of the 'Tessar' lens is discussed by Nasse,[11] 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.

Small body means small lens and means small sensor, so to keep smartphones slim and light, the smartphone manufacturers use a tiny sensor usually less than the 1/2.3" used in most bridge cameras. At one time only Nokia 808 PureView used a 1/1.2" sensor, almost twice the size of a 1/2.3" sensor. Bigger sensors have the advantage of better image quality, but with improvements in sensor technology, smaller sensors can achieve the feats of earlier larger sensors. These improvements in sensor technology allow smartphone manufacturers to use image sensors as small as 1/4" without sacrificing too much image quality compared to budget point & shoot cameras.[12]

Active area of the sensor

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For calculating camera angle of view one should use the size of active area of the sensor. Active area of the sensor implies an area of the sensor on which image is formed in a given mode of the camera. The active area may be smaller than the image sensor, and active area can differ in different modes of operation of the same camera. Active area size depends on the aspect ratio of the sensor and aspect ratio of the output image of the camera. The active area size can depend on number of pixels in given mode of the camera. The active area size and lens focal length determines angles of view.[13]

Sensor size and shading effects

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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.[14] 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 where wpixel 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 where wphotoreceptor is the width of the photoreceptor and (f/#)microlens is the f-number of the microlens.

In order to avoid shading, therefore

If wphotoreceptor / wpixel = ff, the linear fill factor of the lens, then the condition becomes

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.[a]

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.[b]

Common image sensor formats

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

For interchangeable-lens cameras

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Some professional DSLRs, SLTs and mirrorless cameras use full-frame sensors, equivalent to the size of a frame of 35 mm film.

Most consumer-level DSLRs, SLTs and mirrorless cameras use relatively large sensors, either somewhat under 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 OM System (formerly Olympus) and Panasonic).

As of November 2013, there was only one mirrorless model equipped with a very small sensor, more typical of compact cameras: the Pentax Q7, with a 1/1.7" sensor (4.55 crop factor). See section § Smaller sensors below.

Many different terms are used in marketing to describe DSLR/SLT/mirrorless sensor formats, including the following:

Obsolescent and out-of-production sensor sizes include:

  • 548 mm2 area Leica's M8 and M8.2 sensor (crop factor 1.33). Current M-series sensors are effectively full-frame (crop factor 1.0).
  • 548 mm2 area Canon's APS-H format for high-speed pro-level DSLRs (crop factor 1.3). Current 1D/5D-series sensors are effectively full-frame (crop factor 1.0).
  • 548 mm2 area APS-H format for the high-end mirrorless SD Quattro H from Sigma (crop factor 1.35)
  • 370 mm2 area APS-C crop factor 1.5 format from Epson, Samsung NX, Konica Minolta.
  • 286 mm2 area Foveon X3 format used in Sigma SD-series DSLRs and DP-series mirrorless (crop factor 1.7). Later models such as the SD1, DP2 Merrill and most of the Quattro series use a crop factor 1.5 Foveon sensor; the even more recent Quattro H mirrorless uses an APS-H Foveon sensor with a 1.35 crop factor.
  • 225 mm2 area Four Thirds System format from Olympus (crop factor 2.0)
  • 116 mm2 area 1" Nikon CX format used in Nikon 1 series[17] and Samsung mini-NX series (crop factor 2.7)
  • 43 mm2 area 1/1.7" Pentax Q7 (4.55 crop factor)
  • 30 mm2 area 1/2.3" original Pentax Q (5.6 crop factor). Current Q-series cameras have a crop factor of 4.55.

When full-frame sensors were first introduced, production costs could exceed twenty times the cost of an APS-C sensor. Only twenty full-frame sensors can be produced on an 8 inches (20 cm) silicon wafer, which would fit 100 or more APS-C sensors, and there is a significant reduction in yield due to the large area for contaminants per component. Additionally, full frame sensor fabrication originally required three separate exposures during each step of the photolithography process, which requires separate masks and quality control steps. Canon selected the intermediate APS-H size, since it was at the time the largest that could be patterned with a single mask, helping to control production costs and manage yields.[18] Newer photolithography equipment now allows single-pass exposures for full-frame sensors, although other size-related production constraints remain much the same.

Due to the ever-changing constraints of semiconductor fabrication and processing, and because camera manufacturers often source sensors from third-party 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 of these 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).

Smaller sensors

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Most sensors are made for camera phones, compact digital cameras, and bridge cameras. 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 most compact digital cameras used small 1/2.3" sensors. Such cameras include Canon PowerShot SX230 IS, Fujifilm Finepix Z90 and Nikon Coolpix S9100. Some older digital cameras (mostly from 2005–2010) used even smaller 1/2.5" sensors: these include Panasonic Lumix DMC-FS62, Canon PowerShot SX120 IS, Sony Cyber-shot DSC-S700, and Casio Exilim EX-Z80.

As of 2018 high-end compact cameras using one inch sensors that have nearly four times the area of those equipping common compacts include Canon PowerShot G-series (G3 X to G9 X), Sony DSC-RX100 series, Panasonic Lumix DC-TZ200 and Panasonic DMC-LX15. Canon has an APS-C sensor on its top model PowerShot G1 X Mark III.

For many years until Sep. 2011 a gap 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.

Finally, Sony has the DSC-RX1 and DSC-RX1R cameras in their lineup, which have a full-frame sensor usually only used in professional DSLRs, SLTs and MILCs.

Due to the size constraints of powerful zoom objectives, most current bridge cameras have 1/2.3" sensors, as small as those used in common more compact cameras. As lens sizes are proportional to the image sensor size, smaller sensors enable large zoom amounts with moderate size lenses. In 2011 the high-end Fujifilm X-S1 was equipped with a much larger 2/3" sensor. In 2013–2014, both Sony (Cyber-shot DSC-RX10) and Panasonic (Lumix DMC-FZ1000) produced bridge cameras with 1" sensors.

Since the 2020s sensors of many camera phones has surpassed the size of typical compact cameras. The iPhone 13 released in 2021 has a main camera sensor size of 1/1.9".[19] The Nokia N8 (2010)'s 1/1.83" sensor was the largest in a phone in late 2011. The Nokia 808 (2012) surpasses compact cameras with its 41 million pixels, 1/1.2" sensor.[20] Sensor sizes of 1/2.3" and smaller are common in webcams, digital camcorders and most other small devices.

Medium-format digital sensors

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The largest digital sensors in commercially available cameras are described as "medium format", in reference to film formats of similar dimensions. Although the most common medium format film, the 120 roll, is 6 cm (2.4 in) wide, and is most commonly shot square, the most common "medium-format" digital sensor sizes are approximately 48 mm × 36 mm (1.9 in × 1.4 in), which is roughly twice the size of a full-frame DSLR sensor format.

Available CCD sensors include Phase One's P65+ digital back with Dalsa's 53.9 mm × 40.4 mm (2.12 in × 1.59 in) sensor containing 60.5 megapixels[21] and Leica's "S-System" DSLR with a 45 mm × 30 mm (1.8 in × 1.2 in) sensor containing 37-megapixels.[22] In 2010, Pentax released the 40MP 645D medium format DSLR with a 44 mm × 33 mm (1.7 in × 1.3 in) CCD sensor;[23] later models of the 645 series kept the same sensor size but replaced the CCD with a CMOS sensor. In 2016, Hasselblad announced the X1D, a 50MP medium-format mirrorless camera, with a 44 mm × 33 mm (1.7 in × 1.3 in) CMOS sensor.[24] In late 2016, Fujifilm also announced its new Fujifilm GFX 50S medium format, mirrorless entry into the market, with a 43.8 mm × 32.9 mm (1.72 in × 1.30 in) CMOS sensor and 51.4MP. [25] [26]

Table of sensor formats and sizes

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Different sizes of Omnivision CMOS sensors An OV7910 (1/3") and three OV6920 (1/18") sensors, both types with composite video (NTSC) outputs.

Sensor sizes are expressed in inches notation because at the time of the popularization of digital image sensors they were used to replace video camera tubes. The common 1" outside diameter circular video camera tubes have a rectangular photo sensitive area about 16 mm on the diagonal, so a digital sensor with a 16 mm diagonal size is a 1" video tube equivalent. The name of a 1" digital sensor should more accurately be read as "one inch video camera tube equivalent" sensor. Current digital image sensor size descriptors are the video camera tube equivalency size, not the actual size of the sensor. For example, a 1" sensor has a diagonal measurement of 16 mm.[27][28]

The increasing image sensor sizes used in smartphones plotted
The development of different format image sensors in the main cameras of smartphones

Sizes are often expressed as a fraction of an inch, with a one in the numerator, and a decimal number in the denominator. For example, 1/2.5 converts to 2/5 as a simple fraction, or 0.4 as a decimal number. This "inch" system gives a result approximately 1.5 times the length of the diagonal of the sensor. This "optical format" measure 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 in (9.4 mm); instead, the diagonal is closer to 0.26 in (6.6 mm).[29][30][31] Instead of "formats", these sensor sizes are often called types, as in "1/2-inch-type CCD."

Due to inch-based sensor formats not being standardized, their exact dimensions may vary, but those listed are typical.[30] 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., minimum f-number), but in practice are not directly proportional to image noise or resolution due to other limitations. See comparisons.[32][33] Film format sizes are also included, for comparison. The application examples of phone or camera may not show the exact sensor sizes.

  1. ^ Defined here as the equivalent number of stops lost (or gained, if positive) due to the area of the sensor relative to a full 35 mm frame (36 mm × 24 mm). Computed as
  2. ^ Defined here as the ratio of the diagonal of a full 35 mm frame to that of the sensor format, that is

See also

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Notes

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Footnotes and references

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In digital photography and machine vision systems, an image sensor format refers to the physical dimensions and aspect ratio of the image sensor, which captures light and converts it into electrical signals to produce a digital image. These formats are typically denoted by historical inch-based designations (e.g., 1/2" or 1") derived from the diameters of analog video camera tubes that digital sensors replaced, though the actual sensor dimensions are smaller than the nominal value. The format directly influences key imaging characteristics, including the field of view, light-gathering capability, noise levels, and compatibility with lenses. Common image sensor formats vary widely to suit different applications, from compact consumer devices to professional cinema cameras. The full-frame format, equivalent to 35mm film, measures 36 mm × 24 mm with a 3:2 aspect ratio and a diagonal of approximately 43.3 mm, offering superior low-light performance and shallow due to its large area. Crop sensor formats, which are smaller and multiply the effective of lenses (creating a ""), include (roughly 23.5 mm × 15.6 mm for a diagonal of about 28.2 mm, crop factor ~1.5×) and Micro Four Thirds (17.3 mm × 13.0 mm, 4:3 aspect ratio, crop factor 2×). Smaller formats, such as 1-inch (13.2 mm × 8.8 mm, crop factor ~2.7×) or 1/2.3-inch (6.17 mm × 4.55 mm, crop factor ~5.6×), are prevalent in smartphones and point-and-shoot cameras for their compactness and cost-effectiveness, though they generally exhibit higher in low light compared to larger sensors. The choice of sensor format balances trade-offs in system design, such as lens size and cost, with larger formats requiring wider lens elements to cover the and enabling higher and resolution potential without increasing excessively. In professional applications, formats like (exceeding 36 mm × 24 mm, e.g., 44 mm × 33 mm) provide even greater detail and color fidelity for high-end and . Standardization of these formats ensures between sensors, lenses, and camera bodies across manufacturers, though variations exist due to designs.

Fundamentals of Image Sensor Formats

Definition and Characteristics

An format refers to the physical dimensions, including width and height, and the of the photosensitive area within a digital sensor, such as those employed in (CCD) or complementary metal-oxide-semiconductor () technologies. This format defines the overall shape and size of the sensor's active surface, which captures incoming light and converts it into electrical signals for . The dimensions are conventionally measured in millimeters, with the diagonal length serving as a standard metric for specifying the sensor's scale, often rooted in historical conventions where sizes are denoted as fractions of an inch—for instance, a "1-inch" format corresponds to a diagonal of approximately 16 mm. Key characteristics of image sensor formats include their aspect ratios, which represent the proportional relationship between the sensor's width and height, influencing the shape of the captured image. Common aspect ratios encompass 3:2, prevalent in still photography for its compatibility with traditional formats; 4:3, typical in compact and medium-format digital cameras; and 16:9, optimized for video applications. Additionally, the format governs the potential pixel count, as the total resolution is determined by the physical area divided by the pitch—the center-to-center between adjacent , usually ranging from 2 to 30 micrometers. Larger formats support either denser arrays for higher resolution or wider pitches for improved light-gathering efficiency, as a greater surface area collects more photons per exposure. In and , the image format fundamentally shapes system design by dictating lens compatibility, as the must align with the lens's projected to avoid , and by influencing the field of view for a fixed lens. This role extends to overall architecture, where format selection balances portability, cost, and application-specific needs without directly addressing downstream performance metrics. The foundational types—CCD and —underpin these formats: CCDs operate by sequentially transferring accumulated charge across the array to a single output , ensuring uniform response but requiring external processing; in contrast, integrate amplification, , and analog-to-digital conversion directly at each , enabling lower power consumption and on-chip functionality.

Historical Development

The development of image sensor formats originated in the 1970s with pioneering (CCD) prototypes. In 1975, engineer assembled the first functional prototype, incorporating a Fairchild 100x100 CCD sensor that yielded approximately 0.01 megapixels of resolution. This innovation laid the groundwork for , drawing inspiration from analog standards, particularly the 35mm format's 36x24mm frame, which later shaped the full-frame digital sensor dimensions to ensure lens compatibility and optical familiarity. During the 1990s and 2000s, sensor formats advanced to support both professional and digital single-lens reflex (DSLR) cameras. Nikon debuted the format in 1999 with the D1, employing a 23.7x15.6mm CCD sensor that cropped the 35mm by a 1.5x factor, enabling affordable high-performance imaging. Canon followed in 2002 by introducing full-frame sensors in the EOS-1Ds, featuring an 11.1-megapixel 35.8x23.8mm sensor that matched the 35mm film's imaging area for unaltered lens perspectives. Concurrently, compact sensor formats proliferated in point-and-shoot cameras, typically measuring around 1/2.3-inch (6.17x4.55mm), prioritizing portability over light-gathering capacity. The 2010s brought standardization and miniaturization, with the Micro Four Thirds format emerging in 2008 through a collaboration between Olympus and , utilizing a 17.3x13mm (2x ) to foster compact mirrorless systems with interchangeable lenses. sensors, meanwhile, continued to shrink, reaching 1/2.5-inch sizes (approximately 5.76x4.29mm) and below by the mid-decade, accompanied by pixel pitches as small as 1μm to accommodate megapixel counts exceeding 12 in slim devices. These developments balanced gains against reduced per-pixel light sensitivity. By the 2020s up to 2025, stacked architectures have facilitated high-resolution medium-format sensors, such as the 102-megapixel 44 mm × 33 mm back-illuminated stacked design in Fujifilm's GFX100 II, released in 2023, which enhances readout speeds for professional stills and video. Global shutter implementations have also advanced for video-centric applications, notably Sony's full-frame stacked sensor in the 2023 Alpha 9 III, enabling distortion-free capture at up to 120 frames per second. In the consumer sector, sensor sizes have grown during the 2020s, with flagship devices such as the 14 Ultra (2024) and Huawei Pura 80 Ultra (2025) featuring 1-inch sensors (diagonal ≈16 mm) to enhance low-light performance and image quality.

Physical Dimensions and Optical Interactions

Sensor Size and Aspect Ratios

Image sensor formats are typically described by their physical dimensions, including horizontal, vertical, and diagonal measurements, expressed either in millimeters for precision or in an archaic inch-based system derived from early video technology. The inch designations originated from vidicon tubes used in 1950s television cameras, where the nominal "inch" size referred to the outer tube diameter rather than the active imaging area; for instance, a "1-inch" vidicon had an effective picture area with a diagonal of approximately 16 mm. In modern digital sensors, this convention persists, so a "1-inch" sensor measures 13.2 mm horizontally by 8.8 mm vertically, yielding a diagonal of about 15.9 mm, despite no actual dimension reaching 25.4 mm. These measurements define the overall format, influencing the sensor's compatibility with lens image circles and the geometric projection of light onto the sensing surface. Aspect ratios, expressed as the proportion of width to height, further shape the format's geometry and dictate how scenes are framed directly from the sensor without post-capture cropping. The 3:2 ratio, standard in digital single-lens reflex cameras, mirrors the dimensions of traditional and provides a balanced horizontal emphasis suitable for landscapes and portraits, capturing wider scenes relative to height. In contrast, the 4:3 ratio, used in Four Thirds systems, offers a more square-like framing that preserves vertical detail for subjects like or macro work, reducing the need to crop for square compositions. The 16:9 widescreen ratio, prevalent in video-oriented sensors, stretches horizontal coverage for cinematic or broadcast applications, enabling immersive wide-angle views but potentially compressing vertical elements in still imaging. These ratios directly affect compositional framing by altering the field of view's proportions, allowing photographers to select formats that align with intended aspect without losing resolution to crops. Sensors are classified by size based on diagonal dimensions, with full-frame formats measuring 36 mm × 24 mm, corresponding to a 43.3 mm diagonal that matches the exposure area of . sensors exceed this scale, typically featuring diagonals greater than 43 mm—such as 48 mm × 36 mm with a 60 mm diagonal—to accommodate expansive imaging for professional applications requiring heightened detail. Smaller formats, often under 20 mm diagonal, include compact types like the 1-inch sensor at 15.9 mm, which enable portable devices but constrain the angular coverage compared to larger counterparts. Variations in format design include non-square pixels in certain video sensors, where individual pixels have unequal horizontal and vertical dimensions to match display standards like or PAL, optimizing data efficiency without altering the overall sensor shape. Emerging experimental formats, such as curved sensors, deviate from flat planes to better mimic biological eyes and reduce optical aberrations; as of 2025, prototypes like NHK's 0.01 mm-thick bendable sensors demonstrate viability for wide-field imaging but remain in research stages.

Active Sensing Area

The active sensing area of an refers to the central region composed of the photosite array, where individual s—each containing a such as a —capture incident light and convert it into electrical charge, excluding non-photosensitive elements like peripheral borders, interconnect wiring, and integrated amplifiers. This area is distinct from the overall sensor die, as the latter includes supporting circuitry that does not contribute to detection. The efficiency of light capture within each is quantified by the fill factor, defined as the ratio of the light-sensitive surface area to the total area, which typically ranges from 60% to 90% in modern sensors depending on pixel design and illumination architecture. In sensor architecture, the active sensing area is primarily the pixel array, while peripheral circuitry—such as row and column decoders, analog-to-digital converters, and timing controllers—occupies the borders around it, potentially comprising 10-20% of the total die in compact designs. Back-illuminated sensors (BSI), introduced commercially by in 2009 for applications, relocate metal wiring and transistors to the front side while illuminating the photodiodes from the back, thereby increasing the effective active area and fill factor by reducing light obstruction and improving quantum efficiency to over 90% in some cases. This design shift, building on research from the early , minimizes shadowing from overlying structures and enhances light collection without altering the physical layout. Inactive borders in small-format sensors proportionally reduce the effective active sensing area relative to the quoted die dimensions, as circuitry overhead consumes a larger fraction of the limited space; for instance, a nominally "1-inch" sensor, derived from historical vidicon tube specifications, has an actual active diagonal of approximately 15.9 mm rather than a full 25.4 mm. This discrepancy arises because the designation refers to the outer tube diameter, not the -capturing region, leading to a smaller usable area that impacts light-gathering capacity and format equivalence. Such borders can also introduce minor shading effects at the periphery due to uneven light falloff near non-sensitive zones. Recent advancements in organic image sensors and 3D-stacked CMOS designs have pushed active area utilization toward near-100% fill factors by decoupling photosensitive layers from underlying electronics. Organic photodiodes, overlaid directly on CMOS readout circuits, enable full-surface light detection without gaps for transistors, achieving up to 100% geometric fill factor as demonstrated in hybrid prototypes since the early 2020s. Similarly, post-2020 3D-stacked architectures vertically integrate logic and memory layers beneath the pixel array using through-silicon vias, freeing the top surface for maximum photodetector coverage and supporting higher-resolution formats with minimal efficiency loss.

Crop Factor and Equivalence

The crop factor, also known as the format factor or focal length multiplier, is defined as the ratio of the diagonal dimension of a full-frame (35 mm) sensor, approximately 43.3 mm, to the diagonal dimension of the sensor in question. This ratio quantifies how a smaller sensor "crops" the image projected by a lens compared to the full-frame standard, effectively narrowing the field of view. The formula for calculating the crop factor is crop factor=43.3sensor diagonal (mm)\text{crop factor} = \frac{43.3}{\text{sensor diagonal (mm)}}. For example, an APS-C sensor with a diagonal of about 28.3 mm yields a crop factor of approximately 1.5×, while a Micro Four Thirds (MFT) sensor with a 21.6 mm diagonal results in a 2× crop factor. Equivalence principles extend the to predict how images from different formats can be made comparable in terms of angle of view, , and exposure. To achieve an equivalent angle of view, the of a lens on a cropped is multiplied by the ; for instance, a 50 mm lens on an produces a similar to a 75 mm lens on full-frame. For equivalence, the must also be scaled by the , such that an f/2 on an MFT (2× crop) matches the of an f/4 on full-frame. These scalings derive from and ensure that photographic parameters like , , and ISO are adjusted proportionally to the format diagonal for equivalent results across . In practical photography applications, the crop factor leads to a narrower on smaller sensors, which can simulate longer focal lengths without physically longer lenses, beneficial for telephoto work but challenging for wide-angle shots. Regarding exposure equivalence, larger sensors collect more total photons for the same scene and exposure settings due to their greater area, improving even if per-unit-area light density remains constant. Limitations of the crop factor concept arise when applied to sensors larger than full-frame, such as , where the falls below 1× (e.g., 0.79× for a 44 × 33 mm ), inverting the equivalence and widening the field of view relative to full-frame. Additionally, digital cropping within a further increases the effective , but this does not alter the physical 's light-gathering capacity.

Impacts on Image Quality

Depth of Field Effects

Depth of field (DoF) refers to the range of distances within a scene that appear acceptably sharp in an image. Image sensor format plays a key role in determining DoF through its influence on the crop factor and the circle of confusion (CoC), which defines the maximum acceptable blur for perceived sharpness. Smaller sensor formats, with higher crop factors, yield deeper DoF for equivalent framing and aperture compared to larger formats like full-frame, as the relative CoC is larger on smaller sensors, extending the zone of sharpness. This scaling with crop factor means that achieving the same field of view on a smaller sensor requires a shorter focal length, which inherently deepens DoF at the same f-stop. The HH, the closest focus distance at which DoF extends to , illustrates this effect and is calculated as H=f2Nc,H = \frac{f^2}{N \cdot c}, where ff is the , NN is the , and cc is the CoC diameter. For larger sensors, cc is larger (e.g., 0.03 mm vs. 0.02 mm for ) to ensure equivalent sharpness when images are viewed at standard sizes, resulting in a shorter and thus shallower overall DoF. A practical comparison highlights these differences: a 50 mm f/1.8 lens on a full-frame produces a shallower DoF than the same lens on an (1.5x ) for the same subject distance, due to the narrower on the smaller , which provides a tighter framing equivalent to a longer on full-frame. To match both the tighter framing and the shallower DoF of the full-frame 50mm f/1.8 on , the setup would need approximately a 50 mm f/1.2 lens, demonstrating how full-frame allows shallower DoF at equivalent f-numbers for the same wide-angle framing, but for equivalent framing, smaller sensors require wider apertures for similar background blur. This capability of full-frame sensors enables more pronounced and creamy bokeh effects, providing an advantage in genres requiring subject isolation. In genres like portraiture and , the deeper DoF of smaller sensors limits and subject isolation, often requiring photographers to stop down less or use closer distances to approximate the possible on larger formats. In contrast, benefits from this trait in compact cameras, where deeper DoF maintains focus across moving subjects and backgrounds, reducing the need for continuous refocusing in dynamic scenes. To counteract deeper DoF on smaller sensors, faster lenses with maximum apertures like f/1.2 or f/1.4 are employed to widen the relative to equivalence, enabling shallower focus. As of 2025, AI-based post-processing mitigates this further by simulating defocus blur and from in-focus images through depth estimation and generative models.

Diffraction and Resolution Limits

imposes a fundamental optical limit on the resolution achievable by image sensors, arising from the wave nature of as it passes through the lens . The smallest resolvable detail is determined by the , the diffraction pattern produced by a of , with its radius given approximately by r1.22λNr \approx 1.22 \lambda N, where λ\lambda is the of (typically around 550 nm for visible ) and NN is the of the lens. The limit occurs when the Airy disk size becomes comparable to or larger than the pitch, causing overlapping patterns that blur fine details across multiple pixels. In image sensors, smaller formats with higher pixel densities exacerbate this limit because they employ finer pixel pitches, leading to diffraction effects at wider apertures compared to larger sensors. For instance, compact sensors with 1 μm pixels encounter significant diffraction softening at f/2.8, where the Airy disk diameter spans multiple pixels and reduces effective resolution, whereas full-frame sensors with typical 5-6 μm pixels can maintain sharpness up to f/11 before similar impacts. Thus, full-frame sensors generally provide sharper details due to reduced diffraction limitations at common apertures compared to smaller sensors with higher pixel densities. This interaction highlights how sensor size indirectly influences the usable aperture range: smaller sensors hit the diffraction barrier sooner when pursuing high resolution through dense pixel arrays. Resolution metrics, such as modulation transfer function (MTF) curves, quantify this softening by illustrating how diffraction attenuates contrast at high spatial frequencies. Diffraction causes a characteristic roll-off in MTF beyond the cutoff frequency, approximately fc=1/(λN)f_c = 1 / ( \lambda N ), blurring edges and fine textures in a manner independent of lens aberrations but directly tied to aperture and wavelength. Practically, this sets pixel density limits; for example, 100 MP full-frame sensors (with ~3 μm pixels) remain viable for professional use at common apertures like f/5.6-f/8, preserving usable MTF above 50% at Nyquist frequencies, while 200 MP compact sensors on smartphone formats (~0.6 μm pixels) suffer pronounced softening even at f/1.8-f/2, limiting real-world detail extraction despite raw pixel counts. Advancements in sensor design incorporate filters to suppress artifacts in high-density arrays, allowing operation closer to the limit without excessive moiré, while post-processing software in tools like Canon Digital Photo Professional and DxO PhotoLab applies targeted algorithms to partially restore contrast lost to diffraction, extending the effective resolution range for small-format sensors.

Lens Image Circle Compatibility

The of a lens is defined as the of the illuminated circular area projected onto the focal plane, which must fully encompass the 's active area to ensure complete coverage without geometric truncation. For a full-frame with dimensions of 36 mm × 24 mm, the required image circle is approximately 43.3 mm, matching the sensor's diagonal measurement. In contrast, an , typically sized around 23.5 mm × 15.6 mm, necessitates an of about 28 mm to cover its diagonal. Sensor format significantly influences lens design trade-offs, as smaller formats like APS-C enable lenses with reduced image circle requirements, leading to more compact optics with fewer and smaller glass elements, thereby lowering manufacturing costs, weight, and overall size. Larger formats, such as full-frame or medium format, demand expansive image circles that necessitate bulkier, heavier lenses with additional corrective elements, escalating production expenses and physical demands on camera systems. Compatibility between lenses and sensors hinges on image circle size relative to format; full-frame lenses, with their broader coverage, seamlessly pair with smaller sensors without coverage shortfalls. However, lenses on full-frame bodies often result in incomplete sensor illumination, causing edge cutoff, which can be mitigated through in-camera modes that digitally restrict the active area to the lens's diameter. As of 2025, lens design evolutions emphasize modularity for hybrid sensor formats, with interchangeable optical modules enabling adjustable s to accommodate varying sensor sizes in compact devices like smartphones. Additionally, architectures are gaining prominence in , providing parallel chief rays for uniform sensor coverage across formats, minimizing in precision applications.

Noise and Performance Metrics

Exposure and Photon Collection

The total number of photons collected by an depends on the sensor's active area, the at the (determined by scene and lens ), the exposure time, and the sensor's quantum efficiency, which represents the fraction of incident photons converted to photoelectrons. For silicon-based sensors common in , quantum efficiency typically ranges from 50% to 90% across the , with higher values achievable in back-illuminated designs. The relationship can be expressed as: N=ηAEthνN = \eta \cdot A \cdot \frac{E \cdot t}{h \nu} where NN is the number of photoelectrons, η\eta is the quantum efficiency, AA is the sensor area, EE is the illuminance, tt is the exposure time, and hνh\nu is the photon energy. This equation highlights that, for a fixed illuminance and exposure duration, photon collection scales directly with sensor area. Larger sensor formats collect more total light under identical f-stop and scene conditions because the f-number governs illuminance uniformly across the focal plane, while the increased area captures a greater aggregate photon flux. This advantage enables larger sensors to achieve equivalent signal strength at lower ISO sensitivities, reducing the need for amplification and thereby preserving exposure latitude before noise becomes prominent. For instance, a full-frame sensor (approximately 864 mm²) gathers roughly four times the light of a Micro Four Thirds sensor (approximately 225 mm²) for the same settings, equivalent to a 2-stop advantage in light collection. This greater photon collection contributes to cleaner low-light performance in full-frame sensors compared to smaller formats. Within the exposure triangle—comprising , , and ISO—sensor size indirectly influences effective capture by altering total light gathered without changing per-unit-area exposure. With identical and ISO settings, a larger yields a higher total signal from the same , effectively providing greater headroom for post-processing while maintaining consistent image brightness after amplification. This distinction underscores how sensor format adapts the triangle's outcomes, prioritizing total volume over localized intensity.

Noise Sources and Mitigation

Image sensors are susceptible to several primary noise sources that degrade signal quality, with their prominence influenced by sensor format size. Shot noise, arising from the random arrival of photons, follows Poisson statistics where the noise standard deviation is σ=N\sigma = \sqrt{N}
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