Digital camera sensors which are available in couple of types like CCD, Super CCD and APS (CMOS or JFET LBCAT) can affect night and low-light photography in different angles. Here are some major factors that will be affected by sensor size and type:

* Crop Factor & Focal Length Multiplier
* Lens Size & Weight Considerations
* Depth of Field prerequisite
* Depth of Field equivalents
* Pixel Size
* Noise Levels
* Dynamic Range
* Cost of Sensors followed by Digital camera costs
* Diffraction

* Pixel Size
* Noise Levels
* Dynamic Range

Choosing the right camera sensor for night and low-light photography

35.8x23.9mm sensor size is known as 'full frame' for the dimensions it shares with traditional 35mm film. It captures more light, permitting wider angles of view and giving photographers the scope for tighter control over depth of field. Full frame sensors help realize the potential of SLR lenses for low-light and night photographers like never before but why is that and is there draw backs ?!

One major drawback is the crop factor which does not exist in full frame sensors. And you have to carry longer and more costly lenses to cover the same long distance view. As of the low-light and night photography point of view, long distance shooting is not that concerned and photographer is focused on low noise, high quality short distance shots not to mention letting in more light to have more control over exposure settings.

Choosing the right sensor size usually takes place in DSLR cameras while in compact digital cameras image quality and mega-pixel count is more concerned. There are currently 3 sensor sizes that are used more often in DSLR cameras. The 4/3" sensors, the APS or DX size sensors (about 23mmx15mm) and the full frame sensors (35.8x23.9mm) which resemble the exposed area of the silver halide in 35mm film cameras.

Larger sensors normally have larger pixels. this statement is not always true but works most of the time. Larger pixels have the potential to produce lower image noise and have a higher dynamic range. Larger dynamic range means being able to capture shadow and highlight detail at the same time. The bigger the difference between the darkest and brightest areas a sensor can capture at the same time, the larger its dynamic range. Since larger pixels have a greater volume which is followed by a greater range of photon capacity can lead to a higher dynamic range.

The dynamic range of the sensor will determine how much brighter the brightest captured highlight detail can be compared to the darkest captured shadow detail, while the ADC (analog to digital converter) only determines the number of tones in between.
Digital camera sensors consist of pixels with photodiodes which convert the energy of the incoming photons into an electrical charge. The electrical charge is converted to a voltage which is amplified to a level at which it can be processed further by the analog to digital converter (ADC).

Larger pixels receive a greater flow of photons in a given exposure time and at the same aperture value, so their light signal is much more sensitive and stronger. For a given amount of background noise, this produces a higher signal to noise ratio which results in a less sharp photo.

This statement is not always true since the amount of background noise also depends on sensor manufacturing process and how efficiently the camera extracts tonal (ADC) information without introducing additional noise from each pixel. Generally, the abovementioned declaration is more acceptable. Another considerable issue is even if two sensors have the same apparent noise when viewed at 100%, the sensor with the higher pixel count will produce a more robust and clean looking final print. This is because with same print size, the noise gets enlarged less for the higher pixel count sensor, consequently this noise has a higher occurrence and thus appears in finer digital noise dots or grains.

Mr. Jeff Medkeff in his "Using Image Calibration to Reduce Noise in Digital Images" states that;

• Dark noise: Dark noise is an accumulation of heat-generated electrons in the sensor, which end up in the photosites and contribute a snow-like appearance to the image. The related term "dark current" refers to the rate of generation of these electrons, most of which come from boundaries between silicon and silicon dioxide in the sensor.

• Readout noise aka Bias Noise: Constructing an image from the sensor's photosites requires that the charge in each photosite be measured, and converted to a digital value. Making this measurement is part of the process of "reading out" the sensor. But doing so is an imperfect process. The amount of charge in the photosite is too small to be measured without prior amplification, and this is the main source of trouble: no perfect amplifier has been invented, and the amplifiers used on digital imaging sensors add a little bit of noise, similar to static in a radio signal, to the charge they are amplifying. The readout amplifier in a sensor is the main contributor to readout noise.

• Photon noise, aka Poisson noise: Photon noise is caused by the differences in arrival time of light to the sensor. If photons arrived at a constant rate, as though they were being delivered to the photosite by a conveyor belt at an efficient factory, then there would be no photon noise. But that isn't how it works. Photons arrive at the photosite irregularly. One pixel might be lucky enough to be hit with 100 photons in a given amount of time, while its neighbor only receives 80. If the photo is of an evenly illuminated surface, this photon noise will show up as one pixel having an improperly low value compared to an adjacent one.

• Random noise: The remaining noise is traceable to erroneous fluctuations in voltage or current in the camera's circuitry, to electromagnetic interference, and who-knows-what. Random noise will vary from image to image and is a result of many influences. One of the most significant might be random variation in the way electronic components operate at different times, temperatures, and conditions. Whatever the case, random noise is almost always infinitesimal - in most modern digital cameras, random noise will not be detectable in an 8-bit image; it may be barely measurable in a 16-bit image but will very rarely be visible in a conventional photo."

As you see different noise sources exist and there are different ways to eliminate them but the most known digital noise which is produced at high ISO settings can be eliminated through better consideration of sensor size. The larger the sensor size the more it can capture light which gives you more control over ISO setting plus larger pixels which will reduce noise and grains at camera level.

Last but not least I have to mention that as a relatively new technology; Foveon sensors have drawbacks such as relatively low-light sensitivity which omits them from our low-light and night photography digital camera list. To learn more about Foveon sensors read our article regarding different sensor types and manufacturers.